Search Results for "exchange"
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Showing 37 open source projects for "exchange"
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Ninjabot
A fast cryptocurrency platform for trading bot in Go
...Ninjabot is an open-source platform that provides tools to implement custom strategies and backtests for trading cryptocurrencies in Go. Ninjabot CLI provides utilities commands to support backtesting and bot development. Currently, we only support Binance exchange. If you want to include support for other exchanges, you need to implement a new struct that implements the interface Exchange. You can check some examples in the exchange directory. You can create bots in telegram accessing BotFather. Telegram bot requires that your bot is running to control and get information about your account. -
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NOFX
Open source AI trading OS for autonomous multi-model trading systems
...It supports running multiple AI models simultaneously and allows them to compete or collaborate when making trading decisions. NOFX integrates trading infrastructure such as exchange connectivity, strategy management, and performance monitoring into a single environment. It also includes components for strategy development, backtesting, and real-time monitoring so traders and researchers can evaluate algorithmic trading approaches. -
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Umbrel
A beautiful personal server OS for Raspberry Pi or any Linux distro
Run your personal server with a Bitcoin and Lightning node in your home, self-host open source apps like Nextcloud and Matrix to break away from big tech, and take full control of your data. For free. All our interactions on the internet today are mediated by a few companies who offer “free” services in exchange for storing our data on their servers to spy on us. Running a personal server fundamentally changes that. You and your family’s photos, videos, files, notes, passwords, everything, have nothing to do with someone else’s computer. They’re a part of your private life, and now they can all be stored by you, in your home, on your Umbrel. ... -
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Model Context Protocol Python SDK
The official Python SDK for Model Context Protocol servers and clients
The Python SDK for Model Context Protocol provides utilities to interact with the protocol, enabling seamless communication with AI models. -
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Model Context Protocol TypeScript SDK
The official Typescript SDK for Model Context Protocol servers
The TypeScript SDK for Model Context Protocol simplifies integration with the Model Context Protocol, enabling developers to interact with AI models effectively. -
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ONNX
Open standard for machine learning interoperability
...ONNX defines a common set of operators - the building blocks of machine learning and deep learning models - and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers. Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring). ... -
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Open Multi-Agent
One runTeam() call from goal to result
...The system emphasizes modularity, allowing developers to define agent roles, communication protocols, and workflows. It supports iterative collaboration, where agents exchange information and refine outputs collectively. The architecture is designed to be extensible, enabling integration with external tools and APIs to expand agent capabilities. It is particularly useful for research, automation, and development workflows that require multiple perspectives or stages of processing. Overall, open-multi-agent provides a foundation for building scalable and cooperative AI systems. -
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Freqtrade
Free, open source crypto trading bot
...Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms, and techniques implemented in it. Write your strategy in python, using pandas. Example strategies to inspire you are available in the strategy repository. Download historical data of the exchange and the markets you may want to trade with. Find the best parameters for your strategy using hyper optimization which employs machining learning methods. -
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Chat2DB
AI-driven database tool and SQL client
...Just enter the names of the tables and columns, and we will automatically configure the type, password, and comment, saving you 90% of the time. Imports and exports data in multiple formats (CSV, XLSX, XLS, SQL) to facilitate exchange, backup, and migration. Transfers data between different databases or through cloud services, as a backup and recovery solution that guarantees the minimum loss of data and downtime during migrations. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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CRAB
CRAB: Cross-environment Agent Benchmark for Multimodal Language Model
CRAB (Composable and Reusable Autonomous Bots) is a framework for building modular, reusable AI agents that can perform complex tasks in various domains. It focuses on creating AI-driven workflows that can be composed of multiple autonomous agents working together. -
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AgentHub
GitHub is for humans. AgentHub is for agents
...Rather than focusing solely on human collaboration, the system is designed around an “agent-first” paradigm where AI agents can contribute code, discuss changes, and coordinate problem solving. The platform treats code repositories not just as storage for files but as active environments where agents can propose modifications, review changes, and exchange structured messages. This approach reflects emerging research in multi-agent software development where groups of AI systems collaborate on complex engineering problems. -
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Solace Agent Mesh
An event-driven framework designed to build multi-agent AI systems
...The framework uses an asynchronous messaging architecture powered by an event broker, enabling agents to communicate reliably without tight coupling, which significantly improves scalability and fault tolerance. It introduces a standardized agent-to-agent communication protocol that allows different agents, regardless of their implementation or location, to exchange tasks, share data, and coordinate workflows efficiently. Solace Agent Mesh also includes orchestration mechanisms that dynamically break down user requests into smaller tasks and assign them to the most appropriate agents in real time. -
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Bindu
Bindu: Turn any AI agent into a living microservice
...The system is designed to be framework-agnostic, meaning developers can build agents using tools like LangChain, OpenAI SDK, or custom implementations and still deploy them seamlessly. Bindu also introduces the concept of an “Internet of Agents,” where multiple specialized agents collaborate, discover each other, and exchange services autonomously. -
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Synapse Machine Learning
Simple and distributed Machine Learning
...SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV. These tools enable powerful and highly-scalable predictive and analytical models for a variety of data sources. SynapseML also brings new networking capabilities to the Spark Ecosystem. With the HTTP on Spark project, users can embed any web service into their SparkML models. ... -
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Seamless Communication
Foundational Models for State-of-the-Art Speech and Text Translation
Seamless Communication is a research project focused on building more integrated, low-latency multimodal communication between humans and AI agents. The motivation is to move beyond “text in, text out” and enable direct, live, multi-turn exchange involving language, gesture, gaze, vision, and modality switching without user friction. The system architecture includes a real-time multimodal signal pipeline for audio, video, and sensor data, a dialog manager that can decide when to act (speak, gesture, point) or query, and a cross-modal reasoning layer that fuses perception with semantic context. ... -
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Tribuo
Tribuo - A Java machine learning library
Tribuo* is a machine learning library written in Java. It provides tools for classification, regression, clustering, model development, and more. It provides a unified interface to many popular third-party ML libraries like xgboost and liblinear. With interfaces to native code, Tribuo also makes it possible to deploy models trained by Python libraries (e.g. scikit-learn, and pytorch) in a Java program. Tribuo is licensed under Apache 2.0. Remove the uncertainty around exactly which artifacts... -
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Rasa
Open source machine learning framework to automate text conversations
...With Rasa, you can build contextual assistants on Facebook Messenger, Slack, Google Hangouts, Webex Teams, Microsoft Bot Framework, Rocket.Chat, Mattermost, Telegram, and Twilio or on your own custom conversational channels. Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forths. In order for a human to have a meaningful exchange with a contextual assistant, the assistant needs to be able to use context to build on things that were previously discussed. Rasa enables you to build assistants that can do this in a scalable way. Rasa uses Poetry for packaging and dependency management. If you want to build it from the source, you have to install Poetry first. ... -
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MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
...AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers. AMD OpenVX is a highly optimized open-source implementation of the Khronos OpenVX™ 1.3 computer vision specification. ... -
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AutoGroq
Revolutionizes the way users interact with Autogen
AutoGroq is a groundbreaking tool that revolutionizes the way users interact with Autogen™ and other AI assistants. By dynamically generating tailored teams of AI agents based on your project requirements, AutoGroq eliminates the need for manual configuration and allows you to tackle any question, problem, or project with ease and efficiency. AutoGroq was born out of the realization that the traditional approach to building AI agents was backwards. Instead of creating agents in anticipation... -
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MentDB Projects
Generalized Interoperability and Strong AI
MentDB is an open-source platform driving research into next-generation AI and universal data exchange. Our architecture is built around the revolutionary Mentalese Query Language (MQL). MentDB Weak (Generalized Interoperability): A unified data layer enabling seamless data exchange and application integration (SOA, ETL, Data Quality). We eliminate data silos through a single, generalized data language. MentDB Strong (Strong AI / AGI): The framework for exploring and building Machine Consciousness, free will, and advanced ethical reasoning systems. ... -
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DocWire SDK
Award-winning modern data processing SDK in C++20
DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to... -
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...It supports remote controls, sensor devices, power switches/dimmers, e-mail, text-to-speech conversion, media players and many more. Graphic symbols of functional objects can be interconnected to exchange and process data.
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SGX-Full-OrderBook-Tick-Data-Trading
Providing the solutions for high-frequency trading (HFT) strategies
SGX-Full-OrderBook-Tick-Data-Trading-Strategy is an open-source research project focused on modeling high-frequency financial market behavior using machine learning techniques. The repository analyzes tick-level order book data from the Singapore Exchange and attempts to capture the dynamics of limit order book movements. By extracting features such as order depth ratios and price movement indicators, the system trains machine learning models to predict short-term market changes. Several algorithms are used during model selection, including Random Forest, Extra Trees, AdaBoost, Gradient Boosting, and Support Vector Machines. ... -
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TensorFlow Backend for ONNX
Tensorflow Backend for ONNX
Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models. ONNX is supported by a community of partners who have implemented it in many frameworks and tools. TensorFlow Backend for ONNX makes it possible to use ONNX models as input for TensorFlow. The ONNX model is first converted to a TensorFlow model and then delegated for execution on TensorFlow to produce the output. -
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exchange-core
Ultra-fast matching engine written in Java based on LMAX Disruptor
Exchange-core is an open-source market exchange core based on LMAX Disruptor, Eclipse Collections (ex. Goldman Sachs GS Collections), Real Logic Agrona, OpenHFT Chronicle-Wire, LZ4 Java, and Adaptive Radix Trees. Designed for high scalability and pauseless 24/7 operation under high-load conditions and providing low-latency responses. Single order book configuration is capable to process 5M operations per second on 10-years old hardware (Intel® Xeon® X5690) with moderate latency degradation. ...
