Search Results for "can=" - Page 6
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Showing 231 open source projects for "can="
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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canvas-constructor
An ES6 utility for canvas with built-in functions and chained methods
An ES6 utility for canvas with built-in functions and chained methods. Alternatively, you can import canvas-constructor/browser. That will create a canvas with size of 300 pixels width, 300 pixels height. Set the color to #AEFD54. Draw a rectangle with the previous color, covering all the pixels from (5, 5) to (290 + 5, 290 + 5) Set the color to #FFAE23. Set the font size to 28 pixels with font Impact. Write the text 'Hello World!' -
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49 Agents IDE
Open-source 2D IDE for managing AI agents in native CLIs
...The platform is designed to work across multiple machines simultaneously, allowing agents running on different devices or servers to connect to a unified workspace without requiring SSH, which simplifies distributed development workflows. It supports real-time synchronization across devices, meaning users can monitor and control their agents from laptops, tablets, or phones with the same interface. -
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OpenMemory
Local long-term memory engine for AI apps with persistent storage
OpenMemory is a self-hosted memory engine designed to provide long-term, persistent storage for AI and LLM-powered applications. It enables developers to give otherwise stateless models a structured memory layer that can store, retrieve, and manage contextual information over time. OpenMemory is built around a hierarchical memory architecture that organizes data into semantic sectors and connects them through a graph-based structure for efficient retrieval. It supports multiple embedding strategies, including synthetic and semantic embeddings, allowing developers to balance speed and accuracy depending on their use case. ... -
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Rivet
Visual AI IDE for building agents with prompt chains and graphs
...Rivet supports multiple large language model providers and integrates with services such as embeddings and transcription systems, allowing developers to create richer AI-powered features. Its architecture emphasizes composability, where different components like prompts, APIs, and data processing steps can be combined into reusable pipelines. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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. It follows an iterative workflow where generated tests are executed, validated, and refined to ensure they contribute meaningful coverage improvements. ... -
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GitDiagram
AI tool that converts GitHub repositories into interactive diagrams
...These diagrams provide a high-level overview of a codebase, making it easier for developers to explore unfamiliar projects or understand large and complex repositories. Users can interact with the generated diagrams by clicking components to navigate directly to related files or directories within the repository. GitDiagram combines a modern web frontend with a backend service that processes repository data and generates diagrams dynamically. -
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Generative AI for beginners with JS
Join a time-traveling adventure where you meet history’s legends
...Topics covered include prompt engineering, building AI-powered applications, working with structured outputs, integrating retrieval-augmented generation, and enabling tool or function calling in AI systems. The repository focuses specifically on how generative AI can be integrated into web, mobile, or desktop applications using JavaScript frameworks and APIs. -
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AI Agents From Scratch
Demystify AI agents by building them yourself. Local LLMs
...The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external systems, perform reasoning tasks, and execute structured workflows. It focuses on explaining the architecture of agent systems rather than simply providing finished code, making it useful for developers who want to understand how AI agents actually work internally. By building agents incrementally, the project helps learners grasp concepts such as decision loops, task decomposition, and environment interaction. -
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Secure OpenClaw
A personal 24x7 AI assistant like OpenClaw
Secure-OpenClaw is an open-source project designed to transform your everyday messaging apps like WhatsApp, Telegram, Signal, and iMessage into a 24×7 personal AI assistant that can respond to queries, run tasks, remember context, and interact with external services. Unlike a traditional chatbot that lives in a browser or API dashboard, Secure-OpenClaw runs locally or on your chosen infrastructure and listens for messages on channels you already use, giving you an always-on interface to a powerful agent. It leverages Claude and other models to interpret messages and is built to manage persistent memory, scheduled reminders, and integration with hundreds of third-party apps to automate workflows without leaving your chat. ... -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Easy DataSet
A powerful tool for creating datasets for LLM fine-tuning
Easy DataSet is a comprehensive open-source tool designed to make creating high-quality datasets for large language model fine-tuning, retrieval-augmented generation (RAG), and evaluation as easy and automated as possible by providing intuitive interfaces and powerful parsing, segmentation, and labeling tools. It supports ingesting domain-specific documents in a wide range of formats — including PDF, Markdown, DOCX, EPUB, and plain text — and can intelligently segment, clean, and structure content into rich datasets tailored for downstream LLM training needs. The system includes automated question-generation capabilities, hierarchical label trees, and answer generation pipelines that use LLM APIs to produce coherent paired data with customizable templates. Beyond dataset creation, Easy-dataset also provides a built-in evaluation system with model testing and blind-test features, helping teams validate model performance using curated test sets. -
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Firecrawl MCP Server
Adds powerful web scraping and search to Cursor and Claude
...The server is designed to run with Firecrawl’s hosted API or self-hosted deployments, making it flexible for enterprise data-governance requirements. Built-in behaviors include JavaScript rendering, automatic retries, and streamable HTTP so long pages and large crawls can flow incrementally into agents. Because it’s an MCP server, clients get typed inputs/outputs and standardized error handling rather than ad-hoc prompt instructions. The repository is active, widely starred, and includes quick starts that make it easy to add web research to an agent stack. -
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annyang!
Speech recognition for your site
...Use optional words or phrases to define a part of the command as optional. annyang plays nicely with all browsers, progressively enhancing browsers that support SpeechRecognition, while leaving users with older browsers unaffected. Grab the latest version of annyang.min.js, drop it in your html, and start adding commands. You can easily add a GUI for the user to interact with Speech Recognition using Speech KITT. Speech KITT is fully customizable and comes with many different themes, and instructions on how to create your own designs. -
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Harbor LLM
Run a full local LLM stack with one command using Docker
Harbor is an open source, containerized toolkit designed to simplify running local large language model (LLM) environments. It combines a CLI and companion app to launch backends, frontends, and supporting services with minimal setup. With a single command, users can start preconfigured tools like Ollama and Open WebUI, enabling chat, workflows, and integrations immediately. Harbor supports multiple inference engines, including llama.cpp and vLLM, and connects them seamlessly to user interfaces. It also includes tools for web retrieval, image generation, voice interaction, and workflow automation. ... -
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Basic Memory
Persistent AI memory using local Markdown knowledge graphs
...Instead of losing context after each chat, it stores information as simple Markdown files on your device, allowing both you and AI to read and write to the same knowledge base. It uses the Model Context Protocol (MCP) so compatible AI tools can access, update, and build on your notes across sessions. Basic Memory creates a semantic knowledge graph by linking related ideas, making it easier to retrieve, expand, and connect information over time. With a local-first design, your data stays private and portable, while optional cloud sync enables cross-device access. It combines simplicity with powerful indexing and search, giving you a flexible way to build long-term memory for projects, research, and workflows. -
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NOFX
Open source AI trading OS for autonomous multi-model trading systems
...NOFX integrates trading infrastructure such as exchange connectivity, strategy management, and performance monitoring into a single environment. It also includes components for strategy development, backtesting, and real-time monitoring so traders and researchers can evaluate algorithmic trading approaches. -
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LLM Course
Course to get into Large Language Models (LLMs)
...It emphasizes reproducible experiments: each step is demonstrated with runnable code, clear dependencies, and references to commonly used open-source models and libraries. Learners get exposure to multiple adaptation strategies—LoRA/QLoRA, instruction fine-tuning, and alignment techniques—so they can choose approaches that fit their hardware and budgets. The materials also cover inference optimization and quantization to make serving LLMs feasible on commodity GPUs or even CPUs, which is crucial for side projects and startups. Evaluation is treated as a first-class topic, with examples of automatic and human-in-the-loop methods to catch regressions and verify quality beyond simple loss values. ... -
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OpenAI Assistants Quickstart
OpenAI Assistants API quickstart with Next.js
...The primary chat logic lives in the Chat component at app/components/chat.tsx, which manages rendering, streaming, and forwarding function calls. Server handlers for threads are provided under api/assistants/threads/..., giving a reference for wiring the API into Next.js routes. The Chat component can be copied directly into other projects, along with its styles from app/components/chat.module.css. Example pages include a basic chat, a function calling demo, a file search demo, and a full-featured example, allowing developers to explore each feature in isolation or together. -
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natural
General natural language facilities for node
...Russian stemming has been added and Spanish stemming has been added, as well. Stemming and tokenizing in more languages have been added. If you’re just looking to use natural without your own node application, you can install via NPM. -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
...Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher accuracy and 83%+ success on complex workflows. Developers can integrate via Python/TypeScript SDKs or REST API, with support for OpenAI, Claude, Gemini, LangChain, LlamaIndex, and CrewAI. Features include built-in authentication, multi-tenancy, hosted servers, Docker support, and enterprise security guardrails. Licensed under Apache 2.0, Klavis simplifies AI development by eliminating complex authentication management and enabling seamless workflow automation across multiple applications. -
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OpenPromptStudio
Visual editor for AI prompts with translation, categories, and tools
...It supports the creation and classification of prompt segments, allowing users to organize them into different types such as styles, quality modifiers, commands, or general prompt elements. OpenPromptStudio also provides translation capabilities that can convert Chinese prompts into English and display Chinese translations for English prompts, which is especially useful for tools that require English inputs. A built-in prompt dictionary helps users quickly access commonly used prompt fragments and reuse them in different projects. Users can optionally manage and maintain this dictionary using a connected workspace database, enabling more flexible prompt organization. -
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Stake Crash Predictor
Stake Crash Predictor is a toolkit for stake mines predictor & Plinko.
The Stake Crash Predictor is a focused toolkit that combines statistical analysis, optional server fairness seed hash decrypt helpers, and AI-assisted summaries to help you study rounds on Stake.us. This project centers on the stake mines predictor and stake predictor workflows Demo-focused stake crash predictor app — seed-inspection helpers (SHA-512 / SHA-256), AI-assisted summaries, and demo bot templates for stake mines predictor too, Start in demo mode to test safely. Disclaimer:... -
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GNNPCSAFT Chat
Chatbot with GNNPCSAFT
The GNNPCSAFT Chat is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, you can chat with LLM models (Gemini or Ollama) with GNNPCSAFT tools, allowing you to ask questions about the PC-SAFT parameters of various compounds, predict thermodynamic properties, and get insights into the GNNPCSAFT's performance. -
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CodinIT.dev
Free, local, open-source AI app builder
CodinIT.dev is a free, local, open source AI app builder that lets you go from idea to full-stack application entirely on your machine, no coding required, just chat with AI. You can build unlimited apps with real-time previews, instant undo, and responsive, frictionless workflows. Deep Supabase integration means you can create UI and backend logic in one cohesive environment, while the model-agnostic architecture lets you connect to any AI, whether cloud-based (Gemini 3 Pro, GPT-5, Claude Sonnet 4.5) or local via Ollama, so you’re never locked in. ... -
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LIDA
Automatic Generation of Visualizations and Infographics using LLMs
...Instead of requiring users to manually explore datasets and write plotting scripts, LIDA analyzes the data and automatically proposes visualization goals and design ideas that highlight patterns and relationships. The platform can generate visualization code compatible with a wide range of libraries, allowing it to integrate with common data science ecosystems. It also supports iterative workflows where visualizations can be edited, explained, evaluated, and repaired through AI-driven feedback loops. The system is model-agnostic and can connect to multiple language model providers, enabling flexibility across different AI infrastructures. -
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General Knowledge Machine Project
Intellect Modeling Kit: assisting research, diagnostics, consulting
...KM is not intended to replace human experts, it is built to multiply abilities. Machine should not be responsible for decisions. The IMK is designed to create ready-to-use software applications using simple text files. Any human knowledge can be uploaded to KM by expert not familiar with software coding. Demos present in kit. Good luck!
