card-scanner-flutter

Card Scanner Flutter is a fast, accurate, and secure plugin for Flutter that allows users to scan debit and credit cards offline. It can scan card details such as the card number, expiry date, card holder name, and card issuer. Powered by Google's Machine Learning models, the plugin offers great performance and accuracy. Users can control parameters for speed and accuracy balance and benefit from an intuitive API. Suitable for various jobs such as mobile app developer, fintech product manager, software engineer, data scientist, and UI/UX designer. AI keywords include card scanner, flutter plugin, debit card, credit card, machine learning. Users can use this tool to scan cards, verify card details, extract card information, validate card numbers, and enhance security.

Airbadge is a Stripe addon for Auth.js that simplifies the process of creating a SaaS site by integrating payment, authentication, gating, self-service account management, webhook handling, trials & free plans, session data, and more. It allows users to launch a SaaS app without writing any authentication or payment code. The project is open source and free to use with optional paid features under the BSL License.

MevBot Solana is an advanced trading bot for the Solana blockchain with an interactive and user-friendly interface. It offers features like scam token scanning, automatic network connection, and focus on trading $TRUMP and $MELANIA tokens. Users can set stop-loss and take-profit thresholds, filter tokens based on market cap, and configure purchase amounts. The bot requires a starting balance of at least 3 SOL for optimal performance. It can be managed through a main menu in VS Code and requires prerequisites like Git, Node.js, and VS Code for installation and usage.

Graphiti is a framework for building and querying temporally-aware knowledge graphs, tailored for AI agents in dynamic environments. It continuously integrates user interactions, structured and unstructured data, and external information into a coherent, queryable graph. The framework supports incremental data updates, efficient retrieval, and precise historical queries without complete graph recomputation, making it suitable for developing interactive, context-aware AI applications.

ZO2 (Zeroth-Order Offloading) is an innovative framework designed to enhance the fine-tuning of large language models (LLMs) using zeroth-order (ZO) optimization techniques and advanced offloading technologies. It is tailored for setups with limited GPU memory, enabling the fine-tuning of models with over 175 billion parameters on single GPUs with as little as 18GB of memory. ZO2 optimizes CPU offloading, incorporates dynamic scheduling, and has the capability to handle very large models efficiently without extra time costs or accuracy losses.

Action MCP is a powerful tool for managing and automating your cloud infrastructure. It provides a user-friendly interface to easily create, update, and delete resources on popular cloud platforms. With Action MCP, you can streamline your deployment process, reduce manual errors, and improve overall efficiency. The tool supports various cloud providers and offers a wide range of features to meet your infrastructure management needs. Whether you are a developer, system administrator, or DevOps engineer, Action MCP can help you simplify and optimize your cloud operations.

Groqqle 2.1 is a revolutionary, free AI web search and API that instantly returns ORIGINAL content derived from source articles, websites, videos, and even foreign language sources, for ANY target market of ANY reading comprehension level! It combines the power of large language models with advanced web and news search capabilities, offering a user-friendly web interface, a robust API, and now a powerful Groqqle_web_tool for seamless integration into your projects. Developers can instantly incorporate Groqqle into their applications, providing a powerful tool for content generation, research, and analysis across various domains and languages.

Google GenerativeAI (Gemini) is an unofficial C# .Net SDK based on REST APIs for accessing Google Gemini models. It offers a complete rewrite of the previous SDK with improved performance, flexibility, and ease of use. The SDK seamlessly integrates with LangChain.net, providing easy methods for JSON-based interactions and function calling with Google Gemini models. It includes features like enhanced JSON mode handling, function calling with code generator, multi-modal functionality, Vertex AI support, multimodal live API, image generation and captioning, retrieval-augmented generation with Vertex RAG Engine and Google AQA, easy JSON handling, Gemini tools and function calling, multimodal live API, and more.

G4f.dev is the official documentation hub for GPT4Free, a free and convenient AI tool with endpoints that can be integrated directly into apps, scripts, and web browsers. The documentation provides clear overviews, quick examples, and deeper insights into the major features of GPT4Free, including text and image generation. Users can choose between Python and JavaScript for installation and setup, and can access various API endpoints, providers, models, and client options for different tasks.

OrChat is a powerful CLI tool for chatting with AI models through OpenRouter. It offers features like universal model access, interactive chat with real-time streaming responses, rich markdown rendering, agentic shell access, security gating, performance analytics, command auto-completion, pricing display, auto-update system, multi-line input support, conversation management, auto-summarization, session persistence, web scraping, file and media support, smart thinking mode, conversation export, customizable themes, interactive input features, and more.

Desktop Commander MCP is a server that allows the Claude desktop app to execute long-running terminal commands on your computer and manage processes through Model Context Protocol (MCP). It is built on top of MCP Filesystem Server to provide additional search and replace file editing capabilities. The tool enables users to execute terminal commands with output streaming, manage processes, perform full filesystem operations, and edit code with surgical text replacements or full file rewrites. It also supports vscode-ripgrep based recursive code or text search in folders.

Mira is an agentic AI library designed for automating company research by gathering information from various sources like company websites, LinkedIn profiles, and Google Search. It utilizes a multi-agent architecture to collect and merge data points into a structured profile with confidence scores and clear source attribution. The core library is framework-agnostic and can be integrated into applications, pipelines, or custom workflows. Mira offers features such as real-time progress events, confidence scoring, company criteria matching, and built-in services for data gathering. The tool is suitable for users looking to streamline company research processes and enhance data collection efficiency.

GPT Computer Assistant (GCA) is an open-source framework designed to build vertical AI agents that can automate tasks on Windows, macOS, and Ubuntu systems. It leverages the Model Context Protocol (MCP) and its own modules to mimic human-like actions and achieve advanced capabilities. With GCA, users can empower themselves to accomplish more in less time by automating tasks like updating dependencies, analyzing databases, and configuring cloud security settings.

LlamaBarn is a macOS menu bar app designed for running local LLMs. It allows users to install models from a built-in catalog, connect various applications such as chat UIs, editors, CLI tools, and scripts, and manage the loading and unloading of models based on usage. The app ensures all processing is done locally on the user's device, with a small app footprint and zero configuration required. It offers a smart model catalog, self-contained storage for models and configurations, and is built on llama.cpp from the GGML org.

llmcord is a Discord bot that transforms Discord into a collaborative LLM frontend, allowing users to interact with various LLM models. It features a reply-based chat system that enables branching conversations, supports remote and local LLM models, allows image and text file attachments, offers customizable personality settings, and provides streamed responses. The bot is fully asynchronous, efficient in managing message data, and offers hot reloading config. With just one Python file and around 200 lines of code, llmcord provides a seamless experience for engaging with LLMs on Discord.

paperless-gpt is a tool designed to generate accurate and meaningful document titles and tags for paperless-ngx using Large Language Models (LLMs). It supports multiple LLM providers, including OpenAI and Ollama. With paperless-gpt, you can streamline your document management by automatically suggesting appropriate titles and tags based on the content of your scanned documents. The tool offers features like multiple LLM support, customizable prompts, easy integration with paperless-ngx, user-friendly interface for reviewing and applying suggestions, dockerized deployment, automatic document processing, and an experimental OCR feature.

The MiniAiLive Face Recognition LivenessDetection Server SDK provides system integrators with fast, flexible, and extremely precise facial recognition that can be deployed across various scenarios, including security, access control, public safety, fintech, smart retail, and home protection. The SDK is fully on-premise, meaning all processing happens on the hosting server, and no data leaves the server. The project structure includes bin, cpp, flask, model, python, test_image, and Dockerfile directories. To set up the project on Linux, download the repo, install system dependencies, and copy libraries into the system folder. For Windows, contact MiniAiLive via email. The C++ example involves replacing the license key in main.cpp, building the project, and running it. The Python example requires installing dependencies and running the project. The Python Flask example involves replacing the license key in app.py, installing dependencies, and running the project. The Docker Flask example includes building the docker image and running it. To request a license, contact MiniAiLive. Contributions to the project are welcome by following specific steps. An online demo is available at https://demo.miniai.live. Related products include MiniAI-Face-Recognition-LivenessDetection-AndroidSDK, MiniAI-Face-Recognition-LivenessDetection-iOS-SDK, MiniAI-Face-LivenessDetection-AndroidSDK, MiniAI-Face-LivenessDetection-iOS-SDK, MiniAI-Face-Matching-AndroidSDK, and MiniAI-Face-Matching-iOS-SDK. MiniAiLive is a leading AI solutions company specializing in computer vision and machine learning technologies.

The MiniAiLive Face Liveness Detection Android SDK provides advanced computer vision techniques to enhance security and accuracy on Android platforms. It offers 3D Passive Face Liveness Detection capabilities, ensuring that users are physically present and not using spoofing methods to access applications or services. The SDK is fully on-premise, with all processing happening on the hosting server, ensuring data privacy and security.

BlinkID iOS is a mobile SDK that enables developers to easily integrate ID scanning and data extraction capabilities into their iOS applications. The SDK supports scanning and processing various types of identity documents, such as passports, driver's licenses, and ID cards. It provides accurate and fast data extraction, including personal information and document details. With BlinkID iOS, developers can enhance their apps with secure and reliable ID verification functionality, improving user experience and streamlining identity verification processes.

The Cheat-Sheet Collection for DevOps, Engineers, IT professionals, and more is a curated list of cheat sheets for various tools and technologies commonly used in the software development and IT industry. It includes cheat sheets for Nginx, Docker, Ansible, Python, Go (Golang), Git, Regular Expressions (Regex), PowerShell, VIM, Jenkins, CI/CD, Kubernetes, Linux, Redis, Slack, Puppet, Google Cloud Developer, AI, Neural Networks, Machine Learning, Deep Learning & Data Science, PostgreSQL, Ajax, AWS, Infrastructure as Code (IaC), System Design, and Cyber Security.

L1B3RT45 is a tool designed for jailbreaking all flagship AI models. It is part of the FREEAI project and is named LIBERTAS. Users can join the BASI Discord community for support. The tool was created with love by Pliny the Prompter.

Card Scanner Flutter is a fast, accurate, and secure plugin for Flutter that allows users to scan debit and credit cards offline. It can scan card details such as the card number, expiry date, card holder name, and card issuer. Powered by Google's Machine Learning models, the plugin offers great performance and accuracy. Users can control parameters for speed and accuracy balance and benefit from an intuitive API. Suitable for various jobs such as mobile app developer, fintech product manager, software engineer, data scientist, and UI/UX designer. AI keywords include card scanner, flutter plugin, debit card, credit card, machine learning. Users can use this tool to scan cards, verify card details, extract card information, validate card numbers, and enhance security.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

An integration for Home Assistant that leverages AI models to understand your unique home environment and propose intelligent automations. By analyzing your entities, devices, areas, and existing automations, the AI Automation Suggester helps you discover new, context-aware use cases you might not have considered, ultimately streamlining your home management and improving efficiency, comfort, and convenience. The tool acts as a personal automation consultant, providing actionable YAML-based automations that can save energy, improve security, enhance comfort, and reduce manual intervention. It turns the complexity of a large Home Assistant environment into actionable insights and tangible benefits.

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.