Search Results for "can" - Page 55
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Showing 5116 open source projects for "can"
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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s-tui
Terminal-based CPU stress and monitoring utility
...The utility is particularly useful for diagnosing thermal throttling, validating cooling solutions, and evaluating system stability under heavy load conditions. In addition to passive monitoring, s-tui can integrate with external stress tools to actively push the CPU to its limits while simultaneously displaying performance metrics. The software is lightweight, scriptable, and well suited for remote environments such as SSH sessions or small devices like Raspberry Pi. -
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Flower
Real-time monitor and web admin for Celery distributed task queue
Flower is an open-source web application that provides real-time monitoring and administrative control for Celery distributed task queues. It exposes detailed visibility into worker status, task execution history, and queue metrics through an interactive web dashboard. Developers and operators can remotely manage workers by restarting instances, adjusting pool sizes, revoking tasks, or applying rate limits without direct server access. Flower also supports broker monitoring and integrates with authentication providers and Prometheus for metrics export, making it suitable for production environments. The tool communicates with Celery using event streams, allowing near real-time updates on asynchronous workloads. ... -
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micrograd
A tiny scalar-valued autograd engine and a neural net library
...On top of the core autograd “Value” concept, the project includes a small neural network library that lets you define and train simple models with a PyTorch-like feel, including multilayer perceptrons. The repository is intentionally compact and readable, prioritizing clarity over performance so learners can follow every step of gradient flow and parameter updates. It is commonly used as a learning bridge between basic calculus intuition and full-scale deep learning frameworks, helping developers understand why autodiff libraries behave the way they do. -
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Hello-Agents
Building an Intelligent Agent from Scratch
...It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step task execution, enabling hands-on experimentation with modern LLM-powered agent systems. The repository is structured as a progressive learning path, combining theory, exercises, and runnable code so users can incrementally build more capable agents. Its goal is to demystify agent engineering and help developers move from simple prompt scripts to robust autonomous systems. -
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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PageIndex
Document Index for Vectorless, Reasoning-based RAG
...Rather than chunking text and embedding it into a vector database, PageIndex constructs a tree-structured index — similar to a detailed, AI-enhanced table of contents — that a large language model can traverse to locate the most relevant sections of long documents. This reasoning-driven retrieval aligns more naturally with how humans explore complex texts, improving relevance and traceability, especially in professional domains like financial reports, legal contracts, and technical manuals. The project includes example notebooks, scripts for tree generation and search, and support for multiple document formats including PDF and markdown, with tools designed to preserve context and semantic boundaries. -
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ZAPI
ZAPI by Adopt AI is an open-source Python library
...It emphasizes a declarative router and schema model that uses types to define request and response formats, providing clear contracts for frontend and backend teams while automatically generating documentation. Zapi abstracts many repetitive tasks such as validation, authentication flows, and error handling so developers can focus on business logic instead of infrastructure plumbing. 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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AlohaMini
Open-Source Dual-Arm Mobile Robot with Motorized Lift
...AlohaMini also supports internal linking between notes, enabling a web-like connected knowledge space that grows organically as users create and connect ideas. Collaboration features are integrated so teams can share notebooks, leave comments, and work simultaneously on a shared knowledge base without leaving the platform. -
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runprompt
Run LLM prompts from your shell
runprompt is an interactive command launcher and prompt utility that lets users bind shell commands, scripts, and workflows to quick keyboard shortcuts or natural-language queries, helping streamline repetitive terminal tasks and boost developer productivity. It functions as a lightweight, launcher-centric interface where you can type a phrase, partial command, or alias and have RunPrompt suggest or execute relevant actions instantly, reducing the need to memorize long commands or navigate complex directory structures. The project emphasizes extensibility, letting users define custom actions, integrate with existing shell environments, and even leverage fuzzy matching or contextual prompts to narrow down options as you type. ... -
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Agentic Data Scientist
An end-to-end Data Scientist
Agentic Data Scientist is an experimental AI-driven research framework that orchestrates data science workflows through autonomous agents that can reason, plan, and execute complex analytics tasks. Unlike traditional scripted pipelines, this project lets AI agents break down high-level research goals into sub-tasks such as data acquisition, cleaning, modeling, evaluation, and reporting, with minimal human direction. Each agent is designed to independently call functions, interact with data sources, and adapt to uncertainties during processing, enabling iterative refinement of models without manual coordination. ... -
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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8mb.local
Ffree local self hosted video compressor webui
...The emphasis is on minimalism and performance, so it runs efficiently on low-power devices like Raspberry Pis or small containers, making it ideal for home labs or edge deployments. 8mb.local can also notify users of offline devices or connection drops through configurable alerts, helping preempt outages before they become serious. -
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Reader 3
Quick illustration of how one can easily read books together with LLMs
This project is a minimalist, self-hosted EPUB reader designed to help users browse and read EPUB books one chapter at a time through a lightweight local server, making it especially easy to extract or work with chapters in external tools like large language models. It was created primarily as a simple demonstration of how to combine local book reading with LLM workflows without heavy dependencies or complicated setup, and it runs with just a small Python script and a basic HTTP server. The... -
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PocketFlow Tutorial Codebase Knowledge
Codebase to Tutorial
...By crawling code files, extracting higher-level patterns, and using large language models to narrate explanations, the system aims to help developers — especially those new to a codebase — understand unfamiliar projects without manual deep reading. It supports both GitHub URL crawling and local directory analysis, and can tailor output tutorials to different languages, making it accessible for international developers. -
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Spark TTS
Spark-TTS Inference Code
...It uses an efficient single-stream architecture where speech tokens are directly reconstructed from the predictions of an LLM, removing the need for external acoustic models or complex vocoders and making the generation pipeline cleaner and faster. The project supports zero-shot voice cloning, meaning it can imitate a new speaker’s voice without dedicated training for that specific voice, and works across languages, including English and Chinese, even in cross-lingual code-switching scenarios. Spark-TTS allows users to control speech characteristics like gender, pitch, and speaking rate to customize synthesized output and support virtual speaker creation. -
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Open Wearables
Self-hosted platform to unify wearable health data
...This approach allows users to break free from manufacturer lock-in while enabling richer, customizable dashboards, real-time visualizations, and personalized health analytics that match real-world needs rather than a one-size-fits-all model. It provides building blocks for federated data storage, modular device drivers, and plugin frameworks so contributions from different communities can extend capabilities without rewriting core logic. -
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WYGIWYH
A simple but powerful self-hosted finance tracker
...The app supports multiple currencies, customizable transaction types, and built-in tools like dollar-cost averaging tracking to help you see investment activity alongside regular expenses, making it flexible for real world financial situations and global use. Its interface is designed to prioritize clarity and ease of entry, so you can quickly record and review spending without being overwhelmed by features you don’t need. -
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Loggifly
Get Alerts from your Docker Container Logs
...It supports plain text, regex, and multi-line pattern matching, and its flexible alert templating lets operators tailor messages for clarity and context, including attaching relevant log excerpts. Beyond notifications, LoggiFly can take automated actions such as restarting or stopping containers when specific critical patterns are detected, which is especially useful for preventing damage from misbehaving services. -
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StoryMem
Official code for StoryMem: Multi-shot Long Video Storytelling
StoryMem is a narrative-focused memory accumulation system that lets users build, store, and reference past conversational context or story elements with an AI, effectively enabling the AI to maintain and recall personalized story memories or character arcs over time. Instead of treating each interaction as stateless, it tracks user-defined memory nodes, tags, and story threads so that future interactions can draw on established narrative context like character traits, past events, or ongoing plotlines. This makes it especially valuable for applications like AI-enriched storytelling, long-term role-playing, personal journaling assistants, or persistent game worlds where continuity and coherence matter. StoryMem includes tools to define, edit, and review saved memories, letting users manage what should be retained, forgotten, or emphasized in later conversations. -
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LingBot-VLA
A Pragmatic VLA Foundation Model
...Because LingBot-VLA includes not just the model weights but also a full production-ready codebase with tools for data handling, training, and evaluation, developers can adapt it to custom robots or simulation environments efficiently. -
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OpenTinker
OpenTinker is an RL-as-a-Service infrastructure for foundation models
OpenTinker is an open-source Reinforcement Learning-as-a-Service (RLaaS) infrastructure intended to democratize reinforcement learning for large language model (LLM) agents. Traditional RL setups can be monolithic and difficult to configure, but OpenTinker separates concerns across agent definition, environment interaction, and execution, which lets developers focus on defining the logic of agents and environments separately from how training and inference are run. It introduces a centralized scheduler to manage distributed training jobs and shared compute resources, enabling workloads like reinforcement learning, supervised fine-tuning, and inference to run across multiple settings. ... -
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SERA CLI
A tool to use the Ai2 Open Coding Agents Soft-Verified Agents
...It provides a convenient interface for deploying, testing, and using SERA models without needing to write scaffold code from scratch, acting as both a proxy and utility wrapper to simplify workflows that involve large agent models. Through sera-cli, users can connect to local or cloud-hosted SERA deployments, including via Modal for quick GPU provisioning and model caching, which helps accelerate experiments. The project is targeted at practitioners and researchers in the AI space who need a flexible but powerful CLI interface for model invocation, endpoint configuration, and integration with development pipelines. -
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SimpleMem
SimpleMem: Efficient Lifelong Memory for LLM Agents
...It provides easy-to-use APIs for storing structured memory entries, querying those memories using semantic search, and retrieving context to augment prompt inputs for downstream processing. Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory lifecycle—write, index, retrieve, refine—so applications can handle user history, document collections, or dynamic contextual state systematically. It supports customizable embedding models, efficient vector indexes, and relevance weighting, making it practical for building assistants, personal agents, or domain-specific retrieval systems that need persistent knowledge. -
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Recursive Language Models
General plug-and-play inference library for Recursive Language Models
...It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom agents, environments, policy networks, and reward structures while leveraging built-in dataset utilities, logging, and checkpointing for reproducible experiments. RLM also includes integration with popular simulation environments and benchmark suites, giving researchers a ready-made playground for algorithm comparison and performance tracking. -
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Anthropic's Original Performance
Anthropic's original performance take-home, now open for you to try
...The project sets up a baseline performance problem where participants work to reduce simulated “clock cycles” required to run a given workload, effectively challenging them to engineer faster code under constraints. This take-home includes starter code, tests, and tools to debug performance, aiming to measure how effectively one can apply algorithmic improvements and optimizations. Because it’s framed around beating baseline scores — and even outperforming previous automated systems — it encourages both deep knowledge of Python and creative problem-solving. -
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PersonaPlex
PersonaPlex code
PersonaPlex is an open-source real-time conversational speech AI model that goes beyond traditional text chat by providing full-duplex speech-to-speech interaction, meaning it can listen and talk at the same time instead of waiting for you to finish speaking before responding. This architectural approach eliminates awkward pauses and makes conversations feel much more human-like, with natural behaviors such as overlapping speech, interruptions, and fluent turn-taking, traits that traditional AI assistants typically lack. ... -
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Archon
The knowledge and task management backbone for AI coding assistants
...It acts as a backend (including an MCP server) that allows different AI coding tools and assistants to share the same structured context, knowledge base, and task lists, improving consistency, productivity, and collaboration across multi-agent interactions. Users can import documentation, project files, and external knowledge so that assistants like Claude Code, Cursor, or other LLM-powered tools work with up-to-date, project-specific context rather than relying on limited prompt memory. Archon’s UI and APIs are intended to streamline how developers interact with their agents, whether for exploratory coding, automated task execution, or integrated RAG workflows, helping reduce friction between manual coding tasks and AI-generated suggestions.
