Search Results for "g-code" - Page 9
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Showing 785 open source projects for "g-code"
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
...DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and unstructured text, enabling flexible and comprehensive analysis workflows. It integrates execution-based reasoning by generating and running code as part of its analysis process, allowing it to iteratively refine results and produce more accurate outputs. DeepAnalyze provides multiple interaction interfaces, including a web-based UI, a command-line interface, and a Jupyter-style notebook environment for interactive workflows. -
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4M
4M: Massively Multimodal Masked Modeling
...The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things like depth tokenizers, input masks for generation, and CUDA build questions, signaling active research iteration. The design leans into flexibility and steerability, so prompts and masks can shape behavior without bespoke heads per task. ... -
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DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
...According to the authors, they aligned the training setup of V3.2-Exp with V3.1-Terminus so that benchmark results remain largely comparable, even though the internal attention mechanism changes. In public evaluations across a variety of reasoning, code, and question-answering benchmarks (e.g. MMLU, LiveCodeBench, AIME, Codeforces, etc.), V3.2-Exp shows performance very close to or in some cases matching that of V3.1-Terminus. The repository includes tools and kernels to support the new sparse architecture—for instance, CUDA kernels, logit indexers, and open-source modules like FlashMLA and DeepGEMM are invoked for performance. -
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DeepLabCut
Implementation of DeepLabCut
...Please see the original paper and the latest work below! This package is collaboratively developed by the Mathis Group & Mathis Lab at EPFL (releases prior to 2.1.9 were developed at Harvard University). The code is freely available and easy to install in a few clicks with Anaconda (and pypi). DeepLabCut is an open-source Python package for animal pose estimation. -
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Search with Lepton
Lightweight demo to build a conversational AI search engine quickly
...It retrieves information from supported search engines and uses that context to generate responses through a retrieval-augmented generation approach. The implementation is intentionally minimal, containing fewer than 500 lines of code while still providing a complete working example of an AI-powered search system. It includes both a backend service written in Python and a web interface that allows users to interact with the search engine in a conversational format. Developers can configure different search providers and language models through environment variables, making it flexible for experimentation and prototyping. -
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
...That design makes Matrix particularly well-suited for large-batch inference, model benchmarking, data curation, augmentation, or generation — whether for language, code, dialogue, or multimodal tasks. It supports both open-source LLMs and proprietary models (via integration with model backends), and works with containerized or sandboxed environments for safe tool execution or external code runs. -
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WhisperSpeech
An Open Source text-to-speech system built by inverting Whisper
WhisperSpeech is an open-source text-to-speech system created by “inverting” OpenAI’s Whisper, reusing its strengths as a semantic audio model to generate speech instead of only transcribing it. The project aims to be for speech what Stable Diffusion is for images: powerful, hackable, and safe for commercial use, with code under Apache-2.0/MIT and models trained only on properly licensed data. Its architecture follows a token-based, multi-stage pipeline inspired by AudioLM and SPEAR-TTS: Whisper is used to produce semantic tokens, EnCodec compresses the waveform into acoustic tokens, and Vocos reconstructs high-fidelity audio from those tokens. The repository includes notebooks and scripts for inference, long-form synthesis, and finetuning, as well as pre-trained models and converted datasets hosted on Hugging Face. ... -
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VibeThinker
Diversity-driven optimization and large-model reasoning ability
VibeThinker is a compact but high-capability open-source language model released by WeiboAI (Sina AI Lab). It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the “spectrum” phase) and a second stage uses reinforcement techniques (the “signal” phase) to refine toward correctness and strong reasoning. ... -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
The project is the codebase for an AI agent named Cicero developed by Facebook Research. It is designed to play the board game Diplomacy by combining open-domain natural language negotiation with strategic planning. The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. ... -
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OpenAI Agent Skills
Skills Catalog for Codex
...It organizes reusable, task-specific workflows, instructions, scripts, and resources into modular skill folders so that an AI agent can reliably perform complex tasks without repeated custom prompting, making agent behavior more predictable and composable. Each skill is defined with clear metadata and instructions organizing how an AI assistant should complete specific tasks ranging from project management to code generation and documentation assistance. The repository supports community contributions, allowing developers to add new skills or update existing ones to keep the catalog relevant and practical for evolving use cases. -
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Agent S
Agent S: an open agentic framework that uses computers like a human
...It supports flexible deployment via CLI, SDK, or cloud, and integrates with multiple model providers including OpenAI, Anthropic, Gemini, Azure, and Hugging Face endpoints. With optional local code execution, reflection mechanisms, and compositional planning, Agent S provides a scalable and research-driven framework for building advanced computer-use agents. -
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autoresearch for AMD
AI agents running research on single-GPU nanochat training
...The system is built around a minimal structure that includes a data preparation module, a training script that can be modified, and a program specification that guides the agent’s decision-making process. During each iteration, the agent edits the training code, runs an experiment within a fixed time budget, evaluates performance metrics, and decides whether to retain or discard the changes. This loop allows the system to explore a wide range of architectural and hyperparameter configurations without human intervention. The framework emphasizes simplicity and reproducibility, ensuring that experiments are comparable and results are traceable over time. -
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Prompt flow
Build high-quality LLM apps
Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality. -
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magentic
Seamlessly integrate LLMs as Python functions
Easily integrate Large Language Models into your Python code. Simply use the @prompt and @chatprompt decorators to create functions that return structured output from the LLM. Mix LLM queries and function calling with regular Python code to create complex logic. -
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AWS Neuron
Powering Amazon custom machine learning chips
...Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can continue to use the same ML frameworks you use today and migrate your software onto Inf1 instances with minimal code changes and without tie-in to vendor-specific solutions. Neuron is pre-integrated into popular machine learning frameworks like TensorFlow, MXNet and Pytorch to provide a seamless training-to-inference workflow. It includes a compiler, runtime driver, as well as debug and profiling utilities with a TensorBoard plugin for visualization. -
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SAM 2
The repository provides code for running inference with SAM 2
SAM2 is a next-generation version of the Segment Anything Model (SAM), designed to improve performance, generalization, and efficiency in promptable image segmentation tasks. It retains the core promptable interface—accepting points, boxes, or masks—but incorporates architectural and training enhancements to produce higher-fidelity masks, better boundary adherence, and robustness to complex scenes. The updated model is optimized for faster inference and lower memory use, enabling real-time... -
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CLI-Anything
Making ALL Software Agent-Native
...The system provides a methodology and tooling for generating CLI wrappers around existing applications, allowing them to be controlled programmatically using natural language instructions interpreted by AI agents. It integrates with multiple AI platforms such as Claude Code, OpenClaw, Codex, and GitHub Copilot CLI, enabling cross-platform compatibility and flexibility. CLI-Anything emphasizes structured outputs such as JSON to reduce parsing complexity and improve reliability in automation scenarios. -
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HackerRepo.org
Collection of cybersecurity-related references, scripts, tools, code
HackerRepo is a massive curated repository that aggregates thousands of cybersecurity, ethical hacking, and digital forensics resources into a single structured knowledge base. The project is designed as a companion learning hub for security professionals, penetration testers, and researchers who want organized access to tools, references, and training material. It spans both offensive and defensive security topics, including exploit development, threat hunting, reverse engineering, AI... -
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AgenticSeek
Fully Local Manus AI. No APIs, No $200 monthly bills
AgenticSeek is a fully local autonomous AI assistant designed as a privacy-focused alternative to cloud-based agent platforms. It runs entirely on the user’s hardware and can autonomously browse the web, write code, and plan multi-step tasks without sending data to external services. The system is optimized for local reasoning models and emphasizes zero cloud dependency to maintain full user control. AgenticSeek includes intelligent agent selection, allowing it to determine the best internal agent to handle a given request. It also supports hands-free workflows such as automated web form interaction and information extraction. ... -
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Agent Development Kit (ADK)
Open-source, code-first Python toolkit for building, evaluating, etc.
ADK (Android Device Key) Python is a reference implementation by Google for working with Android attestation keys in Python. It facilitates the integration of Android attestation features into backends or systems that require verification of device identity and integrity. This is especially important in high-security applications where verifying that a device is genuine and uncompromised is critical. ADK Python helps developers verify hardware-backed keys, work with JSON Web Tokens (JWT),... -
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Composio
Composio equip's your AI agents & LLMs
Empower your AI agents with Composio - a platform for managing and integrating tools with LLMs & AI agents using Function Calling. Equip your agent with high-quality tools & integrations without worrying about authentication, accuracy, and reliability in a single line of code. -
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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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Skyvern
Automate browser-based workflows with LLMs and Computer Vision
...Skyvern's AI decisions come with built-in explanations, providing clear summaries and justifications for every action. Support for proxies, with support for country, state, or even precise zip-code level targeting. Skyvern understands how to solve CAPTCHAs to complete complicated workflows. Support for authenticating into user accounts, including support for 2FA/TOTP. Extract data from workflows in any schema of your choice including CSV or JSON. Automate procurement pipelines, breeze through government forms, and complete workflows in any language. -
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deepclaude
Use Claude Code's agent loop with DeepSeek V4 Pro, OpenRouter & more
deepclaude is a lightweight proxy tool that enables developers to run Claude Code’s autonomous coding agent loop using alternative AI backends like DeepSeek V4 Pro, OpenRouter, or other Anthropic-compatible models. It preserves the full Claude Code experience—including file editing, terminal execution, and multi-step agent workflows—while dramatically reducing operational costs. By swapping out the underlying model instead of the interface, deepclaude delivers the same familiar UX with significantly cheaper token pricing. The platform supports seamless backend switching in real time, allowing users to choose between cost efficiency and higher reasoning power when needed. ... -
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openbench
Provider-agnostic, open-source evaluation infrastructure
openbench is an open-source, provider-agnostic evaluation infrastructure designed to run standardized, reproducible benchmarks on large language models (LLMs), enabling fair comparison across different model providers. It bundles dozens of evaluation suites — covering knowledge, reasoning, math, code, science, reading comprehension, long-context recall, graph reasoning, and more — so users don’t need to assemble disparate datasets themselves. With a simple CLI interface (e.g. bench eval <benchmark> --model <model-id>), you can quickly evaluate any model supported by Groq or other providers (OpenAI, Anthropic, HuggingFace, local models, etc.). openbench also supports private/local evaluations: you can integrate your own custom benchmarks or data (e.g. internal test suites, domain-specific tasks) to evaluate models in a privacy-preserving way.
