Search Results for "model-builder"
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Showing 117 open source projects for "model-builder"
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LiveContext
The AI automation platform, self-hosted
LiveContext is a self-hosted AI automation platform that combines chat-driven building, workflows, agents, data tables, and lightweight apps in one environment. Users describe a job conversationally, and the platform turns it into a readable automation graph with scoped AI workers. Each agent can have its own model, tools, files, permissions, credit budget, and audit trail. Workflows can power forms, dashboards, approval screens, and internal tools without requiring a separate app builder. Built-in tables provide searchable and exportable data storage for agents and automations. Operational metrics track calls, token usage, success rates, duration, and per-tool behavior. ... -
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Ghidra MCP
Socket based MCP Server for Ghidra
GhidraMCP is a Ghidra plugin implementing the Model Context Protocol, bridging Ghidra's reverse engineering capabilities with AI assistants to enhance binary analysis tasks. -
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JimuReport
Open source drag-and-drop reporting and dashboard builder platform
JimuReport is an open source data visualization and reporting platform designed to help developers and organizations build reports, dashboards, and large screen data displays through a visual interface. It provides an online report designer that uses an Excel-like editing experience, allowing users to construct reports with drag-and-drop components and cell-based layouts. It focuses on simplifying complex report development by enabling visual configuration instead of manual coding.... -
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Wren Engine
The Semantic Engine for Model Context Protocol(MCP)
Wren Engine is a semantic engine designed to empower Model Context Protocol (MCP) clients and AI agents by providing accurate, contextual, and governed access to business data. It serves as a bridge between large language models (LLMs) and enterprise systems, facilitating seamless integration and interaction. -
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Azure CLI MCP
Talk with Azure using MCP
An MCP server that enables AI assistants to interact with Microsoft Azure via the Azure CLI, allowing tasks such as listing resources, checking configurations, fixing issues, and creating new resources through conversational commands. -
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Wanaku
Wanaku MCP Router
Wanaku is an MCP Router designed to connect AI-enabled applications using the Model Context Protocol. Built on top of Apache Camel and Quarkus, it offers unmatched connectivity, speed, and reliability for AI agents, facilitating seamless integration across various services and platforms. -
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Forge: Magic: The Gathering Rules Engine
An unofficial rules engine for the world's greatest card game
Forge is a comprehensive open-source rules engine and gameplay platform designed to simulate and extend the card game Magic: The Gathering in a fully digital environment. Developed collaboratively by a community of contributors, it implements the vast majority of the game’s rules and card interactions, allowing players to experience both casual and competitive gameplay without official clients. The software supports multiple play modes, including single-player against AI opponents,... -
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JADX-AI-MCP
Plugin for JADX to integrate MCP server
JADX-AI-MCP is an open-source plugin that integrates large language models into the JADX Android decompiler to assist with reverse engineering and code analysis tasks. The project connects JADX with AI assistants through the Model Context Protocol, enabling language models to interact directly with decompiled Android application code. Through this integration, AI systems can inspect classes, analyze methods, retrieve application manifests, and examine other elements of Android packages in real time. The plugin works alongside a companion MCP server that exposes reverse engineering tools to AI clients so they can query and analyze code programmatically. ... -
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Angel
A Flexible and Powerful Parameter Server for large-scale ML
...It is tuned for performance with big data from Tencent and has a wide range of applicability and stability, demonstrating an increasing advantage in handling higher-dimension models. Angel is jointly developed by Tencent and Peking University, taking account of both high availability in industry and innovation in academia. With a model-centered core design concept, Angel partitions the parameters of complex models into multiple parameter-server nodes and implements a variety of machine learning algorithms and graph algorithms using efficient model-updating interfaces and functions, as well as a flexible consistency model for synchronization. Angel is developed with Java and Scala. ... -
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Quarkus MCP Server
This extension enables developers to implement the MCP server
The quarkus-mcp-server is a Quarkus extension that enables developers to implement Model Context Protocol (MCP) server features easily. It provides both declarative and programmatic APIs, simplifying the process of integrating MCP functionalities into Quarkus applications. This extension is part of the Quarkiverse, a hub for Quarkus extensions contributed by the community. -
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Kodezi Chronos
Kodezi Chronos is a debugging-first language model
...Another component, Persistent Debug Memory, allows the system to learn patterns from past debugging sessions and apply that knowledge to future problems. The repository mainly contains research documentation, evaluation benchmarks, and experimental frameworks rather than the full proprietary model implementation. -
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JAI Workflow
Build programmatically custom agentic workflows, AI Agents, RAG system
JAI-Workflow is a framework for building and managing machine learning workflows, streamlining the process from data ingestion to model deployment. -
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FIT Framework
An enterprise-level AI development framework
FIT Framework is an open-source infrastructure designed to support the development, training, and evaluation of machine learning and AI models through a modular and scalable architecture. It aims to streamline the lifecycle of AI systems by providing standardized components for data processing, model training, evaluation, and deployment. The framework is particularly useful for research and production environments where reproducibility and consistency are critical, as it enforces structured workflows and configurable pipelines. It supports experimentation with different models and datasets, allowing developers to iterate quickly while maintaining clear organization of results and configurations. ... -
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RuoYi AI
Enterprise AI platform for building, deploying, and managing apps
RuoYi AI is a full-stack enterprise-oriented AI development platform designed to help developers rapidly build, deploy, and manage intelligent applications using modern large language models and AI ecosystems. It provides a unified framework for integrating multiple AI models from different providers, allowing teams to switch or combine models through a consistent interface without vendor lock-in. RuoYi AI includes built-in support for retrieval-augmented generation, enabling organizations... -
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Agent Development Kit (ADK) for Java
An open-source, code-first Java toolkit
...ADK is designed to be flexible and modular so that developers can build simple automation agents or large distributed agent systems depending on their needs. While it integrates well with Google’s AI ecosystem, the framework is designed to remain model-agnostic and compatible with different machine learning platforms. -
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elasticsearch-learning-to-rank
Plugin to integrate Learning to Rank
The Elasticsearch Learning to Rank plugin uses machine learning to improve search relevance ranking. It's powering search at places like Wikimedia Foundation and Snagajob. -
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Tribuo
Tribuo - A Java machine learning library
...Tribuo's Models, Datasets, and Evaluations have provenance, meaning they know exactly what parameters, transformations, and files were used to create them. Provenance data allows each model to be rebuilt verbatim from scratch and for evaluations to track the models and datasets used for each experiment. -
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Jlama
Jlama is a modern LLM inference engine for Java
...This allows organizations to integrate generative AI features into their systems while maintaining full control over data privacy and infrastructure. The engine supports a wide range of open-source model architectures and formats, including variants of Llama, Mistral, and other transformer-based models. It provides tools for running chat interactions, completing prompts, or exposing an OpenAI-compatible REST API for applications that expect standard LLM endpoints. The project focuses on performance and portability by using native Java optimizations and the Java Vector API to accelerate inference workloads. -
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TorchServe
Serve, optimize and scale PyTorch models in production
TorchServe is a performant, flexible and easy-to-use tool for serving PyTorch eager mode and torschripted models. Multi-model management with the optimized worker to model allocation. REST and gRPC support for batched inference. Export your model for optimized inference. Torchscript out of the box, ORT, IPEX, TensorRT, FasterTransformer. Performance Guide: built-in support to optimize, benchmark and profile PyTorch and TorchServe performance. Expressive handlers: An expressive handler architecture that makes it trivial to support inferencing for your use case with many supported out of the box. ... -
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Deep Java Library (DJL)
An engine-agnostic deep learning framework in Java
Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started. You can use your existing Java expertise as an on-ramp to learn and use machine learning and deep learning. You can use your... -
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Solon
Java enterprise application development framework
Solon is a full-scenario Java enterprise application framework that positions itself as a lean, high-performance alternative to heavy stacks. It advertises large concurrency gains, lower memory use, much faster startup, and dramatically smaller packages while remaining compatible from Java 8 through Java 24. The framework focuses on restrained APIs and an open ecosystem, with modules that cover web, data, cloud, and microservice patterns. Its messaging emphasizes “replaceable Spring”... -
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Astron Agent
Enterprise platform for building and orchestrating AI agent workflows
Astron Agent is an enterprise-grade platform designed for building and managing intelligent AI agent workflows in production environments. It provides a development environment that combines workflow orchestration, model management, and integration with various AI tools and services. Astron Agent enables organizations to design complex agent-driven processes that coordinate models, automation tools, and enterprise systems. It also integrates robotic process automation capabilities so agents can execute tasks across digital systems instead of only generating responses. ... -
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Spring AI Alibaba Examples
Spring AI Alibaba examples for building and testing AI apps
...Each module focuses on a specific use case such as chat, image processing, audio handling, graph workflows, and retrieval-augmented generation. The examples highlight how to integrate AI models, manage prompts, handle memory, and build multi-model or multi-agent workflows. Developers can explore individual project folders for detailed instructions and implementation guidance. Spring AI Alibaba Examples also supports experimentation through playground modules and encourages contributions to expand real-world AI use cases and improve development practices. -
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Stanford CoreNLP
Stanford CoreNLP, a Java suite of core NLP tools
CoreNLP is your one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 6 languages, Arabic, Chinese, English, French, German, and Spanish. The centerpiece of CoreNLP is the pipeline. Pipelines take in raw text,... -
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LangChain for Java
LangChain4j is an open-source Java library
LangChain for Java is an open-source Java framework designed to simplify the development of applications powered by large language models. The library provides a unified API that allows developers to connect Java applications to multiple AI providers and embedding databases without having to implement separate integrations for each service. Its architecture includes abstractions for prompts, chat interactions, document processing, embeddings, and vector storage, enabling developers to build...
