SinkFinder is a tool designed to analyze jar and zip files for security vulnerabilities. It allows users to define rules for white and blacklisting specific classes and methods that may pose a risk. The tool provides a list of common security sink names along with severity levels and associated vulnerable methods. Users can use SinkFinder to quickly identify potential security issues in their Java applications by scanning for known sink patterns and configurations.

Translate texts in manga/images. Some manga/images will never be translated, therefore this project is born. * Image/Manga Translator * Samples * Online Demo * Disclaimer * Installation * Pip/venv * Poetry * Additional instructions for **Windows** * Docker * Hosting the web server * Using as CLI * Setting Translation Secrets * Using with Nvidia GPU * Building locally * Usage * Batch mode (default) * Demo mode * Web Mode * Api Mode * Related Projects * Docs * Recommended Modules * Tips to improve translation quality * Options * Language Code Reference * Translators Reference * GPT Config Reference * Using Gimp for rendering * Api Documentation * Synchronous mode * Asynchronous mode * Manual translation * Next steps * Support Us * Thanks To All Our Contributors :

The 'pictureChange' repository is a plugin that supports image processing using Baidu AI, stable diffusion webui, and suno music composition AI. It also allows for file summarization and image summarization using AI. The plugin supports various stable diffusion models, administrator control over group chat features, concurrent control, and custom templates for image and text generation. It can be deployed on WeChat enterprise accounts, personal accounts, and public accounts.

Ai is a Japanese bot for Misskey, designed to provide various functionalities such as posting random notes, learning keywords, playing Reversi, server monitoring, and more. Users can interact with Ai by setting up a `config.json` file with specific parameters. The tool can be installed using Node.js and npm, with optional dependencies like MeCab for additional features. Ai can also be run using Docker for easier deployment. Some features may require specific fonts to be installed in the directory. Ai stores its memory using an in-memory database, ensuring persistence across sessions. The tool is licensed under MIT and has received the 'Works on my machine' award.

AI Central is a powerful tool designed to take control of your AI services with minimal overhead. It is built on Asp.Net Core and dotnet 8, offering fast web-server performance. The tool enables advanced Azure APIm scenarios, PII stripping logging to Cosmos DB, token metrics through Open Telemetry, and intelligent routing features. AI Central supports various endpoint selection strategies, proxying asynchronous requests, custom OAuth2 authorization, circuit breakers, rate limiting, and extensibility through plugins. It provides an extensibility model for easy plugin development and offers enriched telemetry and logging capabilities for monitoring and insights.

hCaptcha-Solver is an AI-based hcaptcha text challenge solver that utilizes the playwright module to generate the hsw N data. It can solve any text challenge without any problem, but may be flagged on some websites like Discord. The tool requires proxies since hCaptcha also rate limits. Users can run the 'hsw_api.py' before running anything and then integrate the usage shown in 'main.py' into their projects that require hCaptcha solving. Please note that this tool only works on sites that support hCaptcha text challenge.

Lego AI Parser is an open-source application that uses OpenAI to parse visible text of HTML elements. It is built on top of FastAPI, ready to set up as a server, and make calls from any language. It supports preset parsers for Google Local Results, Amazon Listings, Etsy Listings, Wayfair Listings, BestBuy Listings, Costco Listings, Macy's Listings, and Nordstrom Listings. Users can also design custom parsers by providing prompts, examples, and details about the OpenAI model under the classifier key.

This repository provides a comprehensive set of tools for fine-tuning large language models (LLMs) using various techniques, including full parameter training, LoRA (Low-Rank Adaptation), and P-Tuning V2. It supports a wide range of LLM models, including Qwen, Yi, Llama, and others. The repository includes scripts for data preparation, training, and inference, making it easy for users to fine-tune LLMs for specific tasks. Additionally, it offers a collection of pre-trained models and provides detailed documentation and examples to guide users through the process.

RagaAI Catalyst is a comprehensive platform designed to enhance the management and optimization of LLM projects. It offers features such as project management, dataset management, evaluation management, trace management, prompt management, synthetic data generation, and guardrail management. These functionalities enable efficient evaluation and safeguarding of LLM applications.

A script to export the chat history of ChatGPT. Supports exporting to text, HTML, Markdown, PNG, and JSON formats. Also allows for exporting multiple conversations at once.

Qwen AI Free service supports high-speed streaming output, multi-turn dialogue, watermark-free AI drawing, long document interpretation, image parsing, zero-configuration deployment, multi-token support, automatic session trace cleaning. It is fully compatible with the ChatGPT interface. The repository provides various free APIs for different AI services. Users can access the service through different deployment methods like Docker, Docker-compose, Render, Vercel, and native deployment. It offers interfaces for chat completions, AI drawing, document interpretation, image parsing, and token checking. Users need to provide 'login_tongyi_ticket' for authorization. The project emphasizes research, learning, and personal use only, discouraging commercial use to avoid service pressure on the official platform.

GLM AI Free 服务 provides high-speed streaming output, multi-turn dialogue support, intelligent agent dialogue support, AI drawing support, online search support, long document interpretation support, image parsing support. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. The repository also includes six other free APIs for various services like Moonshot AI, StepChat, Qwen, Metaso, Spark, and Emohaa. The tool supports tasks such as chat completions, AI drawing, document interpretation, image parsing, and refresh token survival check.

Spark AI Free 服务 provides high-speed streaming output, multi-turn dialogue support, AI drawing support, long document interpretation, and image parsing. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. The repository includes multiple free-api projects for various AI services. Users can access the API for tasks such as chat completions, AI drawing, document interpretation, image analysis, and ssoSessionId live checking. The project also provides guidelines for deployment using Docker, Docker-compose, Render, Vercel, and native deployment methods. It recommends using custom clients for faster and simpler access to the free-api series projects.

The StepChat Free service provides high-speed streaming output, multi-turn dialogue support, online search support, long document interpretation, and image parsing. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. Additionally, it provides seven other free APIs for various services. The repository includes a disclaimer about using reverse APIs and encourages users to avoid commercial use to prevent service pressure on the official platform. It offers online testing links, showcases different demos, and provides deployment guides for Docker, Docker-compose, Render, Vercel, and native deployments. The repository also includes information on using multiple accounts, optimizing Nginx reverse proxy, and checking the liveliness of refresh tokens.

Functionary is a language model that interprets and executes functions/plugins. It determines when to execute functions, whether in parallel or serially, and understands their outputs. Function definitions are given as JSON Schema Objects, similar to OpenAI GPT function calls. It offers documentation and examples on functionary.meetkai.com. The newest model, meetkai/functionary-medium-v3.1, is ranked 2nd in the Berkeley Function-Calling Leaderboard. Functionary supports models with different context lengths and capabilities for function calling and code interpretation. It also provides grammar sampling for accurate function and parameter names. Users can deploy Functionary models serverlessly using Modal.com.

Pipecat Flows is a framework designed for building structured conversations in AI applications. It allows users to create both predefined conversation paths and dynamically generated flows, handling state management and LLM interactions. The framework includes a Python module for building conversation flows and a visual editor for designing and exporting flow configurations. Pipecat Flows is suitable for scenarios such as customer service scripts, intake forms, personalized experiences, and complex decision trees.

SinkFinder is a tool designed to analyze jar and zip files for security vulnerabilities. It allows users to define rules for white and blacklisting specific classes and methods that may pose a risk. The tool provides a list of common security sink names along with severity levels and associated vulnerable methods. Users can use SinkFinder to quickly identify potential security issues in their Java applications by scanning for known sink patterns and configurations.

Garak is a free tool that checks if a Large Language Model (LLM) can be made to fail in a way that is undesirable. It probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses. Garak's a free tool. We love developing it and are always interested in adding functionality to support applications.

Moonshot is a simple and modular tool developed by the AI Verify Foundation to evaluate Language Model Models (LLMs) and LLM applications. It brings Benchmarking and Red-Teaming together to assist AI developers, compliance teams, and AI system owners in assessing LLM performance. Moonshot can be accessed through various interfaces including User-friendly Web UI, Interactive Command Line Interface, and seamless integration into MLOps workflows via Library APIs or Web APIs. It offers features like benchmarking LLMs from popular model providers, running relevant tests, creating custom cookbooks and recipes, and automating Red Teaming to identify vulnerabilities in AI systems.

SinkFinder + LLM is a closed-source semi-automatic vulnerability discovery tool that performs static code analysis on jar/war/zip files. It enhances the capability of LLM large models to verify path reachability and assess the trustworthiness score of the path based on the contextual code environment. Users can customize class and jar exclusions, depth of recursive search, and other parameters through command-line arguments. The tool generates rule.json configuration file after each run and requires configuration of the DASHSCOPE_API_KEY for LLM capabilities. The tool provides detailed logs on high-risk paths, LLM results, and other findings. Rules.json file contains sink rules for various vulnerability types with severity levels and corresponding sink methods.

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.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Nvidia GPU exporter for prometheus, using `nvidia-smi` binary to gather metrics.

Tracecat is an open-source automation platform for security teams. It's designed to be simple but powerful, with a focus on AI features and a practitioner-obsessed UI/UX. Tracecat can be used to automate a variety of tasks, including phishing email investigation, evidence collection, and remediation plan generation.

OpenInference is a set of conventions and plugins that complement OpenTelemetry to enable tracing of AI applications. It provides a way to capture and analyze the performance and behavior of AI models, including their interactions with other components of the application. OpenInference is designed to be language-agnostic and can be used with any OpenTelemetry-compatible backend. It includes a set of instrumentations for popular machine learning SDKs and frameworks, making it easy to add tracing to your AI applications.

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

Kong, or Kong API Gateway, is a cloud-native, platform-agnostic, scalable API Gateway distinguished for its high performance and extensibility via plugins. It also provides advanced AI capabilities with multi-LLM support. By providing functionality for proxying, routing, load balancing, health checking, authentication (and more), Kong serves as the central layer for orchestrating microservices or conventional API traffic with ease. Kong runs natively on Kubernetes thanks to its official Kubernetes Ingress Controller.