Search Results for "artificial intelligence pentesting" - Page 43
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Showing 7977 open source projects for "artificial intelligence pentesting"
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MongoDB Lens
MongoDB Lens: Full Featured MCP Server for MongoDB Databases
MongoDB Lens is a local Model Context Protocol (MCP) server offering full-featured access to MongoDB databases using natural language via large language models (LLMs). It enables users to perform queries, run aggregations, optimize performance, and more through conversational interactions. -
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MCP BigQuery Server
A Model Context Protocol (MCP) server that provides secure
This MCP server provides secure, read-only access to BigQuery datasets, enabling large language models (LLMs) to safely query and analyze data through a standardized interface. -
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Supabase MCP Server
Query MCP enables end-to-end management of Supabase via chat interface
An open-source MCP server that enables comprehensive management of Supabase projects through natural language interactions, providing capabilities such as SQL execution, schema management, and API integration. -
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OpenDataMCP
Connect any Open Data to any LLM with Model Context Protocol
An initiative aimed at connecting open datasets to Large Language Models (LLMs) using the Model Context Protocol, facilitating seamless access and integration of public data into AI applications. -
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Kubernetes MCP Server
Model Context Protocol (MCP) server for Kubernetes and OpenShift
A powerful and flexible Model Context Protocol (MCP) server implementation designed for seamless integration with Kubernetes and OpenShift environments, enabling enhanced interaction and management capabilities for AI assistants. -
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MCP Server Playwright
MCP server for browser automation using Playwright
An MCP (Model Context Protocol) server that leverages Playwright to provide browser automation capabilities, enabling large language models (LLMs) to interact with web pages, take screenshots, and execute JavaScript within a real browser environment. -
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MCP Teams Server
An MCP (Model Context Protocol) server implementation
An MCP server implementation for Microsoft Teams integration, providing capabilities to read messages, create messages, reply to messages, and mention members, facilitating AI-driven interactions within Teams. -
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Google Calendar MCP
Google Calendar MCP server for Claude Desktop integration
A Model Context Protocol server that allows AI assistants like Claude to interact with Google Calendar, enabling seamless calendar management through natural language conversations. -
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MCP WeComBot Server
An MCP server application that sends various types of messages
An MCP server application that sends various types of messages to the WeCom group robot, facilitating communication between AI assistants and WeCom groups. -
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Embedding Studio
Framework which allows you transform your Vector Database
Embedding Studio is a framework that transforms vector databases into feature-rich search engines. It leverages embeddings to enhance search capabilities, enabling more accurate and context-aware retrieval of information. Embedding Studio supports various data types and integrates seamlessly with existing databases, providing tools for fine-tuning and optimizing embeddings to suit specific application needs. -
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DI-engine
OpenDILab Decision AI Engine
DI-engine is a unified reinforcement learning (RL) platform for reproducible and scalable RL research. It offers modular pipelines for various RL algorithms, with an emphasis on production-level training and evaluation. -
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Classical Language Toolkit (CLTK)
The Classical Language Toolkit
The Classical Language Toolkit (CLTK) is a Python library offering natural language processing support for classical languages, including Latin, Greek, and others. -
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DOLMA
Data and tools for generating and inspecting OLMo pre-training data
DOLMA (Data Optimization and Learning for Model Alignment) is a framework designed to manage large-scale datasets for training and fine-tuning language models efficiently. -
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FastRAG
Efficient Retrieval Augmentation and Generation Framework
fastRAG is a research framework for efficient and optimized retrieval augmented generative pipelines, incorporating state-of-the-art LLMs and Information Retrieval. fastRAG is designed to empower researchers and developers with a comprehensive tool set for advancing retrieval augmented generation. -
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Recognizers-Text
Recognition and resolution of numbers, units, date/time, etc.
Recognizers-Text is a multilingual text recognition library that extracts structured information such as dates, numbers, and currency values from unstructured text. -
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SciSpaCy
A full spaCy pipeline and models for scientific/biomedical documents
ScispaCy is a spaCy extension optimized for processing biomedical and scientific text, providing domain-specific NLP models for tasks like named entity recognition (NER) and dependency parsing. -
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Milvus Bootcamp
Dealing with all unstructured data, such as reverse image search
Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications. -
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Data-Juicer
Data processing for and with foundation models
Data-Juicer is an open-source data processing and augmentation framework designed to enhance the quality and diversity of datasets for machine learning tasks. It includes a modular pipeline for scalable data transformation. -
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LLM CLI
Access large language models from the command-line
A CLI utility and Python library for interacting with Large Language Models, both via remote APIs and models that can be installed and run on your own machine. -
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CodiumAI Cover-Agent
CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation
CodiumAI Cover Agent aims to help efficiently increasing code coverage, by automatically generating qualified tests to enhance existing test suites. -
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Kubeflow Training Operator
Distributed ML Training and Fine-Tuning on Kubernetes
Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and scalable distributed training of machine learning (ML) models created with various ML frameworks such as PyTorch, TensorFlow, XGBoost, MPI, Paddle, and others. -
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pmdarima
Statistical library designed to fill the void in Python's time series
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function. -
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NGBoost
Natural Gradient Boosting for Probabilistic Prediction
ngboost is a Python library that implements Natural Gradient Boosting, as described in "NGBoost: Natural Gradient Boosting for Probabilistic Prediction". It is built on top of Scikit-Learn and is designed to be scalable and modular with respect to the choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this slide deck. -
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MLJ.jl
A Julia machine learning framework
MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing, and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization. -
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Alibi Detect
Algorithms for outlier, adversarial and drift detection
Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. Both TensorFlow and PyTorch backends are supported for drift detection.
