Search Results for "g-code" - Page 38
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Showing 1797 open source projects for "g-code"
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adversarial-spec
A Claude Code plugin that iteratively refines product specifications
adversarial-spec is a framework focused on designing and testing systems using adversarial thinking to uncover weaknesses and improve robustness. It encourages developers to define specifications that anticipate failure modes, edge cases, and malicious inputs before implementing solutions. The project emphasizes proactive design, ensuring that systems are built with resilience in mind from the beginning. It provides structured approaches for identifying vulnerabilities and stress-testing... -
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Ollama JavaScript Library
Ollama JavaScript library
Ollama JavaScript is the official JavaScript client for integrating Ollama into JS and TS applications with a lightweight, developer-friendly API. It is designed around the Ollama REST API, so it feels consistent with the platform while making common tasks easier to handle in application code. The library supports standard chat interactions, text generation, embeddings, and model management, which makes it useful for both simple chat interfaces and more advanced AI-powered workflows. It works in Node.js and also supports browser usage through a dedicated browser import, which broadens where it can be deployed. Streaming responses are built in, returning an async generator so applications can render output progressively instead of waiting for a full response. ... -
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Rust Port
The Rust workspace under rust/ is the current systems-language port
Rust Port is an open-source reconstruction and experimentation framework derived from leaked or reverse-engineered versions of advanced AI coding agents, designed to replicate and extend the capabilities of agentic development systems. It functions as a programmable coding assistant that operates through autonomous workflows, enabling users to generate, modify, and analyze code with minimal manual intervention. The project emphasizes agent-based execution, where tasks are broken down into steps and handled iteratively, simulating how modern AI coding tools operate in production environments. It is often used as a sandbox for exploring how large-scale coding agents behave, including their decision-making processes, tool usage, and workflow orchestration. ... -
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Sunfish
Sunfish: a Python Chess Engine in 111 lines of code
sunfish is a minimalist yet surprisingly strong chess engine written in Python, designed to demonstrate how powerful algorithms can be implemented in a highly compact codebase. Despite being only around a hundred lines of core logic, the engine achieves competitive performance, reaching ratings above 2000 on online platforms. It implements classic chess engine techniques such as alpha-beta pruning and efficient board representation while maintaining readability and simplicity. The project is... -
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TypeAgent Python
Structured RAG: ingest, index, query
...This design allows the system to combine the flexibility of language models with the reliability of traditional programming logic. The repository is intended primarily as a research prototype and sample code rather than a production-ready framework, allowing developers to experiment with building AI agents that maintain structured memory and perform tasks through defined actions. -
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SimpleHTR
Handwritten Text Recognition (HTR) system implemented with TensorFlow
...It also employs connectionist temporal classification (CTC) to align predicted character sequences with input images without requiring character-level segmentation. The repository provides code for training models, performing inference on handwritten text images, and evaluating recognition accuracy. SimpleHTR is commonly used as an educational example for understanding how modern handwriting recognition systems operate. -
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LlamaDeploy
Deploy your agentic worfklows to production
...The project provides an asynchronous architecture that allows developers to deploy complex multi-agent workflows as scalable microservices. It enables teams to move from experimental prototypes to production systems with minimal changes to existing LlamaIndex code, making it easier to operationalize AI agents. The system supports orchestrating multiple services, handling communication between agents, and managing workflow execution in distributed environments. Developers can define workflows that involve multiple steps such as data retrieval, reasoning, tool invocation, and response generation, then deploy them using the framework’s infrastructure tools. ... -
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Floneum
Instant, controllable, local pre-trained AI models in Rust
Floneum is an open-source platform for building AI-powered workflows using large language models through a visual and extensible interface. The system allows users to design complex AI pipelines using a drag-and-drop workflow builder rather than writing extensive code. It focuses on enabling developers and researchers to create language model applications that combine different tools, data sources, and AI capabilities into automated workflows. Floneum supports a plugin architecture that allows external components to extend the platform while maintaining isolation and security. Many plugins can be written in different programming languages and compiled to WebAssembly modules, allowing them to run safely within the system. ... -
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KG-LLM-Papers
Papers integrating knowledge graphs (KGs) and large language models
KG-LLM-Papers is a curated academic resource that collects and organizes research papers exploring the intersection between knowledge graphs and large language models. The repository functions as a continuously updated index of scholarly work that investigates how structured knowledge representations can enhance the reasoning, factual accuracy, and interpretability of language models. It includes surveys, benchmark studies, and cutting-edge research that examine topics such as knowledge... -
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AI Engineering Transition Path
Research papers and blogs to transition to AI Engineering
...Instead of presenting isolated tutorials, the repository provides a structured pathway that guides engineers through the technical knowledge needed to build and deploy large language model systems. The materials include curated research papers, blog posts, and code examples that explain both theoretical foundations and practical implementation strategies. By consolidating these resources into a single repository, the project helps developers navigate the rapidly expanding AI ecosystem without needing to search through scattered materials. -
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All Agentic Architectures
Implementation of 17+ agentic architectures
All Agentic Architectures is an open educational repository that provides hands-on implementations of modern AI agent architectures. The project acts as a practical learning resource that bridges the gap between theoretical research on autonomous agents and real software implementations. It contains more than a dozen agent architectures implemented using frameworks such as LangChain and LangGraph. Each architecture is explained through runnable notebooks that illustrate how the agent works... -
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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
how-to-optim-algorithm-in-cuda is an open educational repository focused on teaching developers how to optimize algorithms for high-performance execution on GPUs using CUDA. The project combines technical notes, code examples, and practical experiments that demonstrate how common computational kernels can be optimized to improve speed and memory efficiency. Instead of presenting only theoretical explanations, the repository includes hand-written CUDA implementations of fundamental operations such as reductions, element-wise computations, softmax, and attention mechanisms. ... -
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LLM Agents Papers
Must-read Papers on LLM Agents
...The project organizes academic literature that explores how language models can act as agents capable of reasoning, planning, and interacting with external tools or environments. Rather than providing software code, the repository functions as a structured knowledge base that helps researchers navigate the rapidly expanding field of agent-based AI research. Papers are categorized into thematic groups covering topics such as tool use, planning algorithms, reasoning strategies, and multi-agent collaboration. The repository helps readers understand how agent architectures are evolving and how they are applied in domains such as robotics, software automation, and decision-making systems. ... -
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Polyaxon
MLOps tools for managing & orchestrating the ML LifeCycle
...Polyaxon integrates seamlessly with Kubernetes and container orchestration so that workloads can be scheduled efficiently, GPU and CPU resources are shared, and distributed training across multiple nodes is straightforward. It supports connection to external Git repositories for source-controlled experiments, making it easy to pull code directly for runs and enabling continuous integration workflows with tools like GitHub Actions. -
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ZAPI
ZAPI by Adopt AI is an open-source Python library
...It integrates smoothly into modern development stacks, supports hot reloading for rapid iteration, and includes a command-line toolchain for scaffolding new endpoints or services with sensible defaults. The framework also supports plugin extensions that add things like rate limiting, caching layers, and telemetry without cluttering core code. -
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TONL
TONL (Token-Optimized Notation Language)
...It provides a serialization format that significantly reduces token usage compared with traditional JSON, which can result in lower costs and more efficient prompt size utilization in LLM-driven systems. TONL isn’t just a format — it includes a rich API for querying, indexing, modifying, and streaming data, along with tools for schema validation and TypeScript code generation. The platform comes with a complete command-line interface that supports interactive dashboards and cross-platform usage in browsers and server environments, and its high test coverage gives developers confidence in stability. -
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Beads
A memory upgrade for your coding agent
...By leveraging Git as the storage backbone, the project ensures that memory is persistent, diffable, and sharable, with the ability to roll back, branch, or merge memory states just like source code. -
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DeployStack
Centralized credential vault, governance, and token optimization
DeployStack is an open-source framework that helps developers and teams define and deploy production infrastructure stacks using modular, reusable templates, often with IaC (infrastructure as code) principles. It provides a structured way to compose resources such as cloud networking, compute, and managed services into coherent deployment blueprints that can be versioned and reused across projects. By abstracting common deployment patterns and capturing them as templates, Deploystack reduces duplication of effort that typically occurs when setting up stacks for different applications or environments. ... -
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D4RL
Collection of reference environments, offline reinforcement learning
D4RL (Datasets for Deep Data-Driven Reinforcement Learning) is a benchmark suite focused on offline reinforcement learning — i.e., learning policies from fixed datasets rather than via online interaction with the environment. It contains standardized environments, tasks and datasets (observations, actions, rewards, terminals) aimed at enabling reproducible research in offline RL. Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm... -
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llmx.txt hub
The largest directory for AI-ready documentation and tools
llms-txt-hub serves as a central directory and knowledge base for the emerging llms.txt convention, a simple, text-based way for project owners to communicate preferences to AI tools. It catalogs implementations across projects and platforms, helping maintain a shared understanding of how LLM-powered services should interact with code and documentation. The repository aims to standardize patterns for allowlists, denylists, attribution, rate expectations, and contact information, mirroring the spirit of robots.txt for the AI era. It provides examples and templates to make adoption straightforward for maintainers of websites, docs portals, and repos. The hub encourages community debate and iteration so conventions remain practical as tooling evolves. ... -
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MCPHub
A unified hub for centralized management and dynamic organization
MCPHub is a unified hub that organizes many MCP servers behind clean Streamable HTTP (SSE) endpoints so clients can connect to “all tools,” a specific server, or logical groups. It’s designed to simplify multi-server operations: one process can multiplex several named STDIO servers and re-expose them over HTTP for IDEs and services. The README ships in multiple languages and includes deployment and routing guidance, signaling an intention to reach a broad user base. The project publishes to... -
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MobileCLIP
Implementation of "MobileCLIP" CVPR 2024
MobileCLIP is a family of efficient image-text embedding models designed for real-time, on-device retrieval and zero-shot classification. The repo provides training, inference, and evaluation code for MobileCLIP models trained on DataCompDR, and for newer MobileCLIP2 models trained on DFNDR. It includes an iOS demo app and Core ML artifacts to showcase practical, offline photo search and classification on iPhone-class hardware. Project notes highlight latency/accuracy trade-offs, with MobileCLIP2 variants matching or surpassing larger baselines at notably lower parameter counts and runtime on mobile devices. ... -
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Anthropic SDK TypeScript
Access to Anthropic's safety-first language model APIs
anthropic-sdk-typescript is the TypeScript / JavaScript client library for the Anthropic REST API, enabling backend or Node.js usage of models like Claude. It wraps API endpoints for creating messages, streaming responses, and managing parameters in a type-safe TS environment. The library is designed for server-side use, interfacing with REST, and is stable for integration in web services or backend agents. Example usage shows how to instantiate the Anthropic client, call... -
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OpenAI Realtime Embedded
Instructions on how to use the Realtime API on Microcontrollers
openai-realtime-embedded is a repository that provides resources, SDKs, and example links for using OpenAI’s Realtime API on embedded hardware platforms (e.g. microcontrollers). The goal is to enable low-latency conversational agents (e.g. voice-based assistants) running directly on constrained devices, by leveraging WebRTC and streaming APIs to communicate with OpenAI systems. The repo includes pointers to an ESP32 implementation (maintained as esp32 branch) and documentation that Espressif... -
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EdgeChains
EdgeChains.js is Full-Stack GenAI library
...We build on top of a tech that has solved this problem in a different domain - Kubernetes Config Management - and bring that to Generative AI. Edgechains is built on top of jsonnet, originally built by Google based on their experience managing a vast amount of configuration code in the Borg infrastructure.
