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This project implements a real-time customer tracking system using computer vision to monitor how long customers spend in a store. It combines YOLO v11m for person detection with DeepSort tracking …
MCP Toolbox for Databases is an open source MCP server for databases.
An example algorithm for a momentum-based day trading strategy.
TradingAgents: Multi-Agents LLM Financial Trading Framework
This project provides an Interactive Brokers (IB) API interface using the Model Context Protocol (MCP).
FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus Agent Tools, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae…
A collection of GPT system prompts and various prompt injection/leaking knowledge.
Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.
🤖 An intelligent stock trading bot combining technical & qualitative analysis with Interactive Brokers TWS API integration
A Python library written to handle IB's Client Portal API, manage portfolio and execute trades.
QAT is a quantum compiler and runtime focused on low-level, just-above-driver integration.
Full stack, modern web application generator. Using FastAPI, MongoDB as database, Docker, automatic HTTPS and more.
Repository for organizing datasets and papers used in Open LLM.
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.
A curated list of awesome decentralized finance projects
Static PyPI package server for personal packages. Uses GitHub pages for hosting.
Your own private PyPi index, github-hosted
The AWS Provider enables Terraform to manage AWS resources.
A solution designed to automate the curation of Amazon AppStream 2.0 Images and allows administrators to create an application repository.
⚡️ The easiest way to build forms with Vue.
Python class for reading GE MUSE XML files. Returns a header with most of the file configurations and the lead's data is available as a Numpy array or a Pandas data frame.