Search Results for "artificial"
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407 projects for "artificial" with 2 filters applied:
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Obsidian Skills
Agent skills for Obsidian
Obsidian-Skills is a repository of agent skills tailored for use with Obsidian and any Claude-compatible agent that follows the standard Agent Skills specification, enabling AI assistants to better understand and interact with Obsidian content. These skills are markdown-driven specifications that teach Claude Code (or similar agents) how to perform context-aware tasks within Obsidian’s unique environment, such as interpreting different file types and workflows, automating workflows tied to... -
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Kodus
AI code reviews, just like your senior dev would do
Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move... -
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PyTensor
Python library for defining and optimizing mathematical expressions
PyTensor is a fork of Aesara, a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays. PyTensor is based on Theano, which has been powering large-scale computationally intensive scientific investigations since 2007. A hackable, pure-Python codebase. Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that... -
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Mistral Inference
Official inference library for Mistral models
Open and portable generative AI for devs and businesses. We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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yt-x
Browse youtube from your terminal
yt-x is a lightweight tool designed to enhance the YouTube viewing and interaction experience by providing additional functionality beyond the standard platform interface. It typically works by injecting scripts or modifying how YouTube pages behave, enabling users to customize playback, interface elements, or interaction features. The project focuses on improving usability and control, allowing users to tailor their viewing experience according to personal preferences. It may include... -
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grammY
The Telegram Bot Framework
grammY makes it easy to create Telegram bots. Both for beginners and at scale. You want grammY because it is easy to use. It is very powerful and always up to date. It has the best documentation in town. It is extremely efficient and scales up effortlessly. It has a thriving ecosystem of plugins, a friendly community chat, seamless integrations with web frameworks and databases, and so much more. -
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AG-UI
The Agent-User Interaction Protocol
AG-UI is an open, lightweight protocol for connecting AI agents to user-facing applications through a standardized event-based interface. It is designed to make agent behavior visible, interactive, and controllable inside real-time front-end experiences. Instead of treating an AI agent as a black-box chat endpoint, AG-UI defines structured events for messages, tool calls, state changes, lifecycle updates, and user interactions. This makes it easier for developers to build agent-powered apps... -
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Agent Executor (AX)
Google's open source distributed agent runtime
Agent Executor (AX) is a Google research project for learning discrete choice models through differentiable maximum likelihood estimation. It is designed for situations where a model needs to predict choices from a finite set of alternatives, such as ranking, recommendation, preference modeling, or decision behavior analysis. The project provides JAX-based tools for defining and training choice models with automatic differentiation. It focuses on flexible model construction rather than a... -
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OpenAI Cookbook
Examples and guides for using the OpenAI API
openai-cookbook is a repository containing example code, tutorials, and guidance for how to build real applications on top of the OpenAI API. It covers a wide range of use cases: prompt engineering, embeddings and semantic search, fine-tuning, agent architectures, function calling, working with images, chat workflows, and more. The content is primarily in Python (notebooks, scripts), but the conceptual guidance is applicable across languages. The repository is kept up to date and often... -
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LLM CLI
Access large language models from the command-line
A CLI utility and Python library for interacting with Large Language Models, both via remote APIs and models that can be installed and run on your own machine. -
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KnowNote
A local-first AI knowledge base & NotebookLM alternative
KnowNote is a local-first, open-source AI knowledge base and notebook application created as an Electron-based alternative to Google NotebookLM that emphasizes privacy, control, and simplicity. It lets users build an intelligent, searchable knowledge base from uploaded documents such as PDFs, Word files, PowerPoints, and web pages, and then interact with that content using LLM-powered chat, summarization, and reasoning tools. Unlike many NotebookLM alternatives that rely on Docker or cloud... -
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QMD
mini cli search engine for your docs, knowledge bases, etc.
QMD is a powerful and lightweight command-line tool that acts as an on-device search engine for your personal knowledge base, allowing you to index and search files like Markdown notes, meeting transcripts, technical documentation, and other text collections without depending on cloud services. Designed to keep all search activity local, it combines classic full-text search techniques with modern semantic features such as vector similarity and hybrid ranking so that queries return not just... -
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Quint Code
Structured reasoning framework for Claude Code, Gemini, and Cursor
Quint Code is a structured reasoning and decision-support framework aimed at making AI-assisted software engineering and decision workflows more rigorous and auditable. It implements the First Principles Framework (FPF) to guide users and AI tools through hypothesis generation, logical verification, evidence gathering, and documented decision making, reducing reliance on ad hoc or “vibe” coding. Instead of accepting the first plausible answer generated by an AI assistant, Quint Code... -
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LLM Datasets
Curated list of datasets and tools for post-training
LLM Datasets curates and standardizes datasets commonly used to train and fine-tune large language models, reducing the overhead of hunting down sources and normalizing formats. The repository aims to make datasets easy to inspect and transform, with scripts for downloading, deduping, cleaning, and converting to formats like JSONL that slot into training pipelines. It highlights instruction-tuning and conversation-style corpora while also pointing to code, math, or domain-specific sets for... -
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Superduper
Superduper: Integrate AI models and machine learning workflows
Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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Loop Engineering
Practical patterns, starters & CLI tools for loop engineering with AI
Loop Engineering is a practical reference repository for designing loop-based workflows with AI coding agents. It focuses on replacing repeated manual prompting with systems that prompt, verify, schedule, and hand off work over time. The project is aimed at developers using tools such as Grok, Claude Code, Codex, Cursor, and other coding agents. It explains core building blocks such as scheduling, worktrees, skills, plugins, connectors, sub-agents, and persistent memory or state. The... -
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mgrep
A calm, CLI-native way to semantically grep everything, like code
This project is a modern, semantic search tool that brings the simplicity of traditional command-line grep to the world of natural language and multimodal content, enabling users to search across codebases, documents, PDFs, and even images using meaning-aware queries. Built with a focus on calm CLI experiences, it lets you index and query your local files with semantic understanding, delivering results that are relevant to your intent rather than simple pattern matches, which is especially... -
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AI Commits
A CLI that writes your git commit messages for you with AI
AI Commits is a command-line tool that writes your git commit messages for you using an AI model. It works by running git diff to gather your staged code changes, sending that diff to an LLM (originally GPT-3, now configurable), and receiving back a concise, human-readable commit message. The tool is designed to integrate cleanly into a developer’s workflow so that generating a descriptive commit message becomes a single command rather than a chore. It supports configuration via environment... -
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FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to... -
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Sourcery AI Code Review
Instant AI code reviews
Sourcery is an AI-powered code assistant designed to help developers write cleaner, more maintainable Python code by suggesting real-time refactorings, improvements, and best-practice rewrites directly in popular editors and IDEs. Instead of just offering autocomplete, Sourcery analyzes existing functions and code patterns to provide context-aware suggestions that can simplify logic, reduce duplication, improve naming, and correct anti-patterns, helping developers adhere to idiomatic style... -
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Courses (Anthropic)
Anthropic's educational courses
Anthropic’s courses repository is a growing collection of self-paced learning materials that teach practical AI skills using Claude and the Anthropic API. It’s organized as a sequence of hands-on courses—starting with API fundamentals and prompt engineering—so learners build capability step by step rather than in isolation. Each course mixes short readings with runnable notebooks and exercises, guiding you through concepts like model parameters, streaming, multimodal prompts, structured... -
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Spring AI
An Application Framework for AI Engineering
Spring AI is a framework within the Spring ecosystem that simplifies the integration of artificial intelligence capabilities into Java applications by providing abstractions over various AI services and models. It is designed to align with familiar Spring development patterns, allowing developers to incorporate AI features such as chat, embeddings, and prompt handling using consistent APIs. The framework supports multiple providers, including OpenAI, Azure OpenAI, and other compatible services, enabling flexibility in deployment strategies. ... -
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ProtoMotions
ProtoMotions is a GPU-accelerated simulation and learning framework
ProtoMotions 3 is a GPU-accelerated framework for training physically simulated digital humans and humanoid robots. It provides modular environments and learning components for animation, robotics, and reinforcement learning research. Large motion datasets such as AMASS and BONES can be divided across multiple GPUs for scalable policy training. A built-in PyRoki workflow retargets human motion data to different robot bodies with a single command. Policies can be tested across Isaac Gym,... -
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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and...
