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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Semantica
Graph-Native Infrastructure for Context and Accountable AI Systems
Semantica is an open-source graph-native infrastructure layer for building explainable and auditable AI systems. It ingests fragmented data, extracts meaningful entities and relationships, and transforms them into context and knowledge graphs. Deterministic reasoning, ontology management, provenance tracking, and decision records help explain how conclusions were reached. The platform can complement existing LLMs, vector databases, and agent frameworks rather than replacing them. It supports... -
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WorkBuddyGuide
A practical, open-source guide to mastering WorkBuddy
WorkBuddy Guide is a community-maintained, open-source practical handbook for learning WorkBuddy through real workplace scenarios. Rather than restating product documentation, it follows tasks from initial setup through repeatable team workflows. The guide covers installation, interface basics, Skills, connectors, APIs, automation, knowledge management, content work, meetings, remote work, and other use cases. Advanced sections address building Skills, multi-agent system design, automation... -
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FlashKDA
High-performance Kimi Delta Attention kernels
FlashKDA is an open-source library of high-performance CUDA kernels for Kimi Delta Attention, implemented on NVIDIA CUTLASS. It is intended to accelerate the forward pass used by KDA-based language models on modern NVIDIA GPUs. The package integrates with flash-linear-attention and can be selected automatically as the backend for chunk_kda during inference. It supports recurrent state input and output, variable-length batches, internal gating, query-key normalization, and beta activation.... -
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Harness Engineering
Field guide, and agent context bundle for harness engineering
Harness Engineering is a retrieval-optimized anthology, field guide, and agent context bundle for improving AI coding-agent performance. It treats the model and agent as fixed while strengthening the surrounding context, tools, constraints, and proof mechanisms. The repository organizes developed arguments, practical cases, source evidence, evaluations, and reusable playbooks into distinct layers. Its agent guide routes each task to the smallest relevant set of materials instead of loading... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Three.js Object Sculptor
Codex plugin that turns attached object images into code-only
Three.js Object Sculptor is a Codex plugin that converts a reference image into a procedural Three.js object written entirely in code. It first evaluates whether the image is suitable and produces an ObjectSculptSpec describing geometry, materials, lighting, hierarchy, pivots, and quality targets. Codex then follows staged passes from blockout and structural work through surface detail, interaction design, and optimization. Generated models include meaningful sockets and anchors for... -
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jlens
Companion code for the global workspace interpretability paper
Jacobian Lens is Anthropic’s reference implementation for examining what a language model’s internal activations are inclined to produce as text. It transports residual-stream vectors from selected layers and positions into the final-layer basis using an averaged input-output Jacobian. The transformed vectors are decoded through the model’s own unembedding into ranked vocabulary predictions. The package can fit new lenses, load saved ones, apply them to prompts, and merge results from... -
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ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
ThinkStats2 is the code and text companion for the second edition of Think Stats, an introduction to statistics and data science for Python programmers. It teaches probability and statistical reasoning through short programs, experiments, and analysis of real datasets. The material emphasizes exploratory methods that help readers ask and answer practical questions with data. Case studies draw from public sources, including health-related datasets, to connect abstract concepts with realistic... -
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TabFM
scikit-learn compatible tabular foundation model
TabFM is a tabular foundation model from Google Research for zero-shot classification and regression on structured datasets. It is designed to work with mixed numerical and categorical columns without requiring a custom training run for every new table. Instead of fitting model weights to the user’s dataset, TabFM uses in-context learning by reading training examples and test rows together at inference time. The library provides scikit-learn-compatible classifier and regressor interfaces,... -
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AI Berkshire
AI-era Berkshire: a value investing research framework
AI Berkshire is an AI-assisted value investing research framework designed for Claude Code and Codex workflows. It turns the investment methods of Warren Buffett, Charlie Munger, Duan Yongping, and Li Lu into structured research agents. The project is meant to improve research depth, decision discipline, and analytical consistency compared with asking a general AI model for a one-off stock opinion. It uses parallel agent analysis, adversarial viewpoints, financial rigor checks, and... -
Build Data Resilience - Take the Assessment TodayIs your recovery strategy as strong as you think? Take this quick self-assessment to check your recovery readiness and gain tailored insights. In only 2 minutes, you'll learn where you fall on the recovery readiness scale.
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DeepSpec
A full-stack codebase for training and evaluating speculative decoding
DeepSpec is a full-stack codebase for training and evaluating draft models used in speculative decoding. It provides the components needed to prepare data, train draft models, and measure acceptance behavior against target models. The workflow starts with data preparation, including prompt download, target answer regeneration, and target cache construction. It then trains a draft model using configuration files for different algorithms and target model setups. The evaluation pipeline... -
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Hy-MT2 is a family of fast-thinking multilingual translation models built for complex real-world translation scenarios. It includes 1.8B, 7B, and 30B-A3B model sizes, giving users options for lightweight deployment, stronger general performance, or MoE-based capacity. The models support translation across 33 languages and are designed to follow detailed translation instructions in multiple languages. They can handle tasks involving terminology, style, personalization, delimiters, structured...
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git-remote-dropbox
A transparent bridge between Git and Dropbox
git-remote-dropbox is a Git remote helper that lets Dropbox act like a real Git remote. It provides a transparent bridge between Git and a Dropbox folder or shared Dropbox folder. After installation and login, users can clone from or push to remote URLs that use the dropbox scheme. The helper preserves traditional Git remote guarantees, including atomic behavior even when multiple people operate on the repository. It can automatically create the repository directory the first time a user... -
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huey
A little task queue for python
huey is a lightweight task queue for Python applications. It gives developers a clean API for running background jobs outside the main request or execution flow. The project supports several storage backends, including Redis, Valkey, Redict, SQLite, the file system, and in-memory storage. It can execute tasks with processes, threads, or greenlets, which makes it adaptable to different workloads. Huey also supports scheduled tasks, recurring tasks, retries, task priorities, result storage,... -
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Make It heavy
A Python framework that emulates Grok Heavy functionality
Make It heavy is a Python framework for producing deeper AI analysis through multi-agent orchestration. It is designed to emulate the style of Grok Heavy by splitting a user query into several specialized research angles. The system runs four agents in parallel so each one can explore the problem from a different perspective. It then combines their outputs into one unified answer through an intelligent synthesis step. The framework uses OpenRouter for model access and can also run in... -
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ZaneOps
A self-hosted PaaS for deploying and managing web apps
ZaneOps is a self-hosted, open-source PaaS for deploying and managing applications, services, databases, workers, and static sites. It is designed as an alternative to platforms like Heroku, Railway, Render, Vercel, and Netlify while keeping ownership of infrastructure in the user’s hands. The platform uses Docker Swarm for scalable container orchestration and Caddy for flexible routing and web serving. It gives developers a polished dashboard for managing projects, deployments, logs, URLs,... -
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Pycorrector
Pycorrector is a toolkit for text error correction
Pycorrector is a Python toolkit for Chinese text error correction. It focuses on common error types such as similar-sounding characters, visually similar characters, grammar issues, proper noun errors, missing words, extra words, wrong words, and word-order problems. The project implements multiple correction approaches, including KenLM, ConvSeq2Seq, BERT, MacBERT, ELECTRA, ERNIE, GPT-style models, and newer Qwen-based correction models. It is designed for use cases such as input method... -
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HRM-Text
1B text generation model based on the HRM architecture
HRM-Text is a one-billion-parameter text generation model and pretraining framework based on the Hierarchical Reasoning Model architecture. It is designed to make foundation model pretraining more accessible by reducing compute and data requirements compared with traditional scaling-heavy approaches. The system combines hierarchical recurrent design, task-completion strengthening, and latent-space reasoning. Its training stack includes PrefixLM sequence packing, FlashAttention 3 kernels,... -
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Dia2
TTS model capable of streaming conversational audio in realtime
Dia2 is a streaming dialogue text-to-speech model created by Nari Labs for generating conversational audio in real time. It is designed to begin producing speech before receiving the entire input text, which makes it useful for interactive voice applications. The model supports audio conditioning, allowing generated speech to follow a reference voice or conversational style more naturally. Dia2 provides 1B and 2B model checkpoints along with inference code for research and experimentation.... -
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GoPay Workflow Orchestrator
Lightweight process orchestration framework for regional payment
GoPay Workflow Orchestrator is a lightweight workflow orchestration framework for studying and debugging regional payment-chain flows. It focuses on engineering reliability in multi-stage payment journeys that involve provider redirects, tokenized requests, verification challenges, asynchronous polling, and final status confirmation. The project organizes scattered payment steps into a reproducible and observable process so developers can inspect state transitions and integration failures.... -
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SkillOpt
Text-space optimizer that trains reusable natural-language skills
SkillOpt is a Microsoft research project for improving frozen LLM agents by optimizing reusable natural-language skill documents. Instead of changing model weights, it treats a compact skill file as the trainable state of the agent. The system learns from agent rollouts, reflection, bounded edits, and validation gates to produce better instructions over time. Its output is a deployable best_skill.md artifact that can be reused across agent tasks. The project is focused on making agents more... -
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Train LLM From Scratch
A straightforward method for training your LLM
Train LLM From Scratch is an educational PyTorch project that shows how to build and train a transformer-based language model from the ground up. It is based on the architecture described in Attention Is All You Need and is designed to make the training pipeline understandable rather than hidden behind a large framework. The repository walks through the process from downloading data to generating text with a trained model. It supports training smaller or larger models, including million- and... -
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Meli-Action
Download files from direct links, YouTube, Telegram, Google Play
Meli-Action is a GitHub Actions-based downloading and web archiving project designed for heavily restricted internet environments. It uses GitHub-hosted workflow runners to fetch content from direct links, YouTube, Telegram, Google Play, SoundCloud, and web pages. Downloaded files are committed into the user’s repository so they can be retrieved later through normal GitHub access. The project includes workflows for different content sources, plus a Python script that can render and save web... -
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Niquests
Drop-in replacement for Requests. Automatic HTTP/1.1, HTTP/2, and HTTP
Niquests is a modern Python HTTP client designed as a drop-in replacement for Requests. It keeps the familiar Requests-style API while adding newer protocol support that the original library does not prioritize. The library can automatically work across HTTP/1.1, HTTP/2, and HTTP/3, and it also includes WebSocket and Server-Sent Events support. Niquests provides both synchronous and asynchronous usage patterns, making it suitable for scripts, backend services, crawlers, API clients, and... -
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blinker-py
Blinker python library for hardware. Works with Raspberry Pi
blinker-py is a Python library for connecting hardware projects to the Blinker IoT platform. It is designed for Raspberry Pi, Banana Pi, Linux devices, and similar single-board or embedded systems. The library helps developers control hardware through the Blinker mobile app, where users can build graphical interfaces with drag-and-drop widgets. It supports common IoT communication patterns such as Wi-Fi, MQTT, WebSocket, and BLE-related platform workflows. The project is useful for makers,... -
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Python Slack SDK
Slack Developer Kit for Python
Python Slack SDK is the official Python developer kit for building applications that interact with the Slack platform. It provides modular packages for Slack APIs, allowing developers to use only the capabilities they need while still keeping the pieces compatible with each other. The SDK covers the Web API, incoming webhooks, Socket Mode, OAuth, Audit Logs, SCIM, RTM, Block Kit models, and request signature verification. It is useful for bots, workflow tools, internal automations, admin...
