Search Results for "no code" - Page 22
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Showing 1865 open source projects for "no code"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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dive-into-llms
"Dive into LLMs" series of practical programming tutorials
...The repository is structured as a learning pathway, making it accessible to both beginners and intermediate practitioners interested in understanding how LLMs work. It includes code samples, tutorials, and conceptual breakdowns that bridge the gap between academic research and real-world implementation. The project also highlights best practices for working with LLMs, including prompt design and optimization strategies. By focusing on clarity and depth, it serves as both a teaching tool and a reference for developers. ... -
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MedgeClaw
Open-source AI research assistant for biomedicine
...It includes a real-time dashboard that displays progress, generated code, and outputs, providing transparency throughout the research process. MedgeClaw also supports reproducibility by generating structured reports and maintaining consistent environments through containerization. Its architecture combines conversational AI, automated pipelines, and scientific tooling into a unified workflow. -
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pua
Your AI has been placed on a PIP. 30 days to show improvement
pua is a high-agency AI skill or plugin designed for use within agent-based coding environments, particularly those like Claude Code, where modular “skills” extend the behavior and capabilities of AI assistants. The project frames the AI as an underperforming senior engineer under evaluation, introducing a strong motivational and behavioral prompt layer that encourages proactive problem-solving and initiative. Rather than adding new technical capabilities, PUA focuses on shaping how the AI approaches tasks, pushing it toward more assertive, autonomous, and results-driven outputs. ... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
...The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval, detection, and segmentation—often requiring little or no fine-tuning. The repository includes code for training, evaluating, and feature extraction, with utilities to run k-NN or linear evaluation baselines to assess representation quality. Pretrained checkpoints cover multiple model sizes so practitioners can trade accuracy for speed and memory depending on their deployment constraints. -
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BioEmu
Inference code for scalable emulation of protein equilibrium ensembles
Biomolecular Emulator (BioEmu for short) is a model that samples from the approximated equilibrium distribution of structures for a protein monomer, given its amino acid sequence. By default, unphysical structures (steric clashes or chain discontinuities) will be filtered out, so you will typically get fewer samples in the output than requested. The difference can be very large if your protein has large disordered regions, which are very likely to produce clashes. BioEmu outputs structures... -
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Airtable MCP
Airtable integration for AI-powered applications
Airtable MCP is an integration tool that enables AI-powered applications to access and manipulate Airtable databases directly from the IDE using Anthropic's Model Context Protocol (MCP). It allows querying, creating, updating, and deleting records using natural language, facilitating seamless data management. -
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MLRun
Machine Learning automation and tracking
MLRun is an open MLOps framework for quickly building and managing continuous ML and generative AI applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications, significantly reducing engineering efforts, time to production, and computation resources. MLRun breaks the silos between data, ML, software, and DevOps/MLOps teams, enabling collaboration and fast continuous... -
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Guardrails
Adding guardrails to large language models
Guardrails is a Python package that lets a user add structure, type and quality guarantees to the outputs of large language models (LLMs). At the heart of Guardrails is the rail spec. rail is intended to be a language-agnostic, human-readable format for specifying structure and type information, validators and corrective actions over LLM outputs. We create a RAIL spec to describe the expected structure and types of the LLM output, the quality criteria for the output to be considered valid,... -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major... -
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Huashu Design
Huashu Design · HTML-native design skill for Claude Code
Huashu-design is a framework focused on designing and optimizing conversational scripts, particularly for persuasive or structured communication scenarios such as sales, marketing, or customer interaction. The project emphasizes the creation of “huashu,” or structured dialogue patterns, that guide interactions toward specific goals. It provides methodologies and tools for organizing conversation flows, ensuring that responses are consistent, effective, and aligned with intended outcomes. The... -
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Fish Speech
SOTA Open Source TTS
Fish Speech is a state-of-the-art open-source text-to-speech project that has evolved into the OpenAudio series of advanced TTS models. The repository hosts the code and tooling for training, fine-tuning, and serving high-quality TTS, while the current flagship models (OpenAudio-S1 and S1-mini) are distributed via Fish Audio’s playground and Hugging Face. The models are evaluated with Seed TTS metrics and achieve exceptionally low word and character error rates, indicating strong intelligibility and alignment between text and audio. ... -
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Antigravity Claude Proxy
Proxy that exposes Antigravity provided claude / gemini models
...This makes it easier to integrate Claude into existing toolchains, scripts, notebooks, or agent frameworks that do not have built-in support for Anthropic’s native SDKs. It abstracts away key differences like authentication choreography, request schema quirks, and streaming protocols so client code can remain unchanged when switching between models. -
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Quadratic
Data science spreadsheet with Python & SQL
...This makes our grids completely portable and very easy to share. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. Quickly write code and see the output in full detail. No more squinting into a tiny terminal to see your data output. -
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Thinc
A refreshing functional take on deep learning
...Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers. -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
...Minisom is designed to allow researchers to easily build on top of it and to give students the ability to quickly grasp its details. The project initially aimed for a minimalistic implementation of the Self-Organizing Map (SOM) algorithm, focusing on simplicity in features, dependencies, and code style. Although it has expanded in terms of features, it remains minimalistic by relying only on the numpy library and emphasizing vectorization in coding style. -
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Kimi K2.5
Moonshot's most powerful AI model
Kimi K2.5 is Moonshot AI’s open-source, native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed vision and text tokens. Based on a 1T-parameter Mixture-of-Experts (MoE) architecture with 32B activated parameters, it integrates advanced language reasoning with strong visual understanding. K2.5 supports both “Thinking” and “Instant” modes, enabling either deep step-by-step reasoning or low-latency responses depending on the task. Designed for... -
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Codey
The home for Codey releases, updates, and the developer community
...Codey combines a fast keyboard-driven TUI with a cross-platform desktop app for developers who want AI assistance close to their coding workflow. It can help read, write, refactor, and inspect code while also running commands and coordinating multi-step engineering tasks. The project uses the Model Context Protocol to connect agent workflows with external tools and richer development context. This repository does not contain the private application source, but it hosts releases, installers, updater metadata, guides, prompts, skills, workflows, issues, and discussions. ... -
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Open Vibe
Open Vibe turns Claude Code into a SaaS-building assistant
Open Vibe is an open-source course and agent workflow that turns Claude Code, Codex, Copilot, Open Code, or another terminal-capable AI coding agent into a SaaS-building assistant. It is built around Open SaaS, a free Wasp-powered SaaS boilerplate, so learners can create a real app while understanding the architecture behind production-ready SaaS systems. The workflow starts with setup instructions that install Node.js, install the Wasp CLI, and verify the local environment. ... -
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Ars Contexta
Claude Code plugin that generates individualized knowledge systems
Ars Contexta is a Claude Code plugin designed to automatically transform conversations into structured, personalized knowledge systems that function as a “second brain.” Instead of leaving insights scattered across chat sessions, the tool captures how a user thinks, works, and solves problems, then converts those interactions into organized markdown files that the user fully owns. -
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Evolver
The GEP-Powered Self-Evolution Engine for AI Agents
...It also depends on Git as part of its operating model, using repository state for rollback, blast-radius calculation, and solidification workflows, which makes it especially relevant for code-centric agent environments. The CLI integrates with external agent runtimes through setup hooks, including support for platforms such as Cursor, where hooks can fire at specific lifecycle moments like session start or after file edits. -
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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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Sandbox Agent
Run Coding Agents in Sandboxes
Sandbox Agent by Rivet is an experimental framework for running AI agents in controlled, isolated environments where they can safely execute code, interact with tools, and perform autonomous tasks without risking system integrity. It is designed to provide a secure sandbox that allows agents to test actions, manipulate files, and run commands while enforcing strict boundaries and monitoring capabilities. The project focuses on enabling more reliable and auditable agent behavior by separating execution from the host environment, which is especially important for applications involving automation, code generation, or system-level operations. ... -
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notebooklm-py
Unofficial Python API and agentic skill for Google NotebookLM
notebooklm-py is an unofficial Python API and agent-ready integration layer for Google NotebookLM that exposes NotebookLM functionality through code, the command line, and AI agent workflows. Its goal is to provide programmatic access not just to standard notebook operations, but also to many capabilities that are either limited or unavailable in the web interface, making it especially useful for automation and custom pipelines. The project covers notebook management, source ingestion, conversational querying, research workflows, and sharing controls, while also enabling the generation of a wide range of study and media artifacts. ... -
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Qodo Cover
AI tool that generates tests to improve code coverage quickly
Qodo Cover is an open source developer tool designed to automate the creation of unit tests using generative AI, helping teams improve code coverage with minimal manual effort. It operates as a command-line interface and can also be integrated into continuous integration workflows, making it adaptable to different development environments. It analyzes an existing codebase, identifies gaps in test coverage, and generates new tests that target uncovered or weakly tested areas. -
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The Hundred-Page Machine Learning Book
The Python code to reproduce illustrations from Machine Learning Book
...The repository complements these explanations by offering practical implementations that demonstrate how various algorithms behave when applied to data. Readers can explore the scripts to reproduce diagrams and observe how mathematical concepts translate into working code.