Search Results for "software without code" - Page 11
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Showing 831 open source projects for "software without code"
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Anything to NotebookLM
Multi-source content processor for NotebookLM
Qiaomu Anything to NotebookLM is a Claude Code skill that turns many types of source material into structured NotebookLM-ready outputs. It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. ... -
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Harness
A meta-skill that designs domain-specific agent teams
...Harness also abstracts the complexity of agent design, making it easier for developers to deploy multi-agent systems without extensive configuration. Its approach emphasizes modularity and reuse, allowing generated agents and skills to be applied across different projects. Overall, Harness acts as an automation layer for building and managing complex agent ecosystems. -
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Sail
A drop-in Apache Spark replacement written in Rust
...It is built entirely in Rust, eliminating JVM overhead and enabling predictable performance, fast startup times, and improved memory safety compared to traditional big data frameworks. Sail is compatible with the Spark Connect protocol, which means existing Spark SQL and DataFrame workloads can run without code changes, making adoption seamless for teams already using Spark-based pipelines. The framework is designed to operate across a variety of environments, including local machines, Kubernetes clusters, and cloud deployments, allowing flexible scaling based on workload requirements. It also emphasizes cost efficiency, with benchmarks showing significant performance improvements and reduced infrastructure usage compared to traditional systems. -
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ChatGPT Exporter
Export and Share your ChatGPT conversation history
ChatGPT Exporter is a browser-based userscript tool designed to export ChatGPT conversations into multiple structured and shareable formats, enabling users to preserve, analyze, and reuse AI-generated content outside the ChatGPT interface. It integrates directly into the ChatGPT web environment, typically via tools like Tampermonkey, and adds export functionality without requiring backend services or complex setup. The tool supports a wide range of output formats including plain text, HTML, Markdown, JSON, and even image-based exports, making it suitable for documentation, knowledge management, and data analysis workflows. One of its key strengths is its ability to preserve formatting such as code blocks, tables, and structured responses, ensuring that exported content remains usable and readable. ... -
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PipesHub
Workplace AI platform for enterprise search and workflow automation
...The platform uses knowledge graphs and ranking algorithms to provide context-rich answers along with traceable sources, improving transparency and trust in AI-generated insights. PipesHub also enables the creation of custom AI agents and applications through a no-code interface, allowing teams to automate workflows and build intelligent tools without deep technical expertise. It supports flexible deployment options, including on-premise and cloud environments, ensuring compatibility with different security and infrastructure requirements. -
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dots.ocr
Multilingual Document Layout Parsing in a Single Vision-Language Model
...The model is designed to recognize virtually any human script, making it highly effective for global and low-resource language scenarios. It achieves state-of-the-art performance on document parsing benchmarks while maintaining a relatively compact model size, demonstrating efficiency without sacrificing accuracy. Beyond standard OCR tasks, it extends its capabilities to parse complex visual elements such as charts, diagrams, and web interfaces, converting them into structured outputs like SVG code. -
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MiniMind-V
"Big Model" trains a visual multimodal VLM with 26M parameters
MiniMind-V is an experimental open-source project that aims to train a very small multimodal vision–language model (VLM) from scratch with extremely low compute and cost, making research and experimentation accessible to more people. The repository showcases training workflows and code designed to produce a 26-million parameter model—including both image and text capabilities—using minimal resources in very little time, reflecting a trend toward democratizing AI research. MiniMind-V combines techniques from modern vision-language modeling but focuses on efficiency and simplicity so that individuals or small teams can explore multimodal learning without massive GPU clusters. ... -
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CutLER
Code release for Cut and Learn for Unsupervised Object Detection
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to... -
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HASH
The best way to use and work with blocks
This is HASH's public monorepo which contains our public code, docs, and other key resources. HASH is a platform for decision-making, which helps you integrate, understand and use data in a variety of different ways. HASH does this by combining various different powerful tools together into one simple interface. These range from data pipelines and a graph database, through to an all-in-one workspace, no-code tool builder, and agent-based simulation engine. These exist at varying stages of... -
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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Tokscale
A CLI tool for tracking token usage from OpenCode, Claude Code
Tokscale is a CLI and terminal UI tool that tracks token usage and estimated cost across multiple AI coding assistants and development workflows. It treats tokens like a measurable resource, helping developers understand how much “AI energy” they are consuming over time and where it is being spent. The tool aggregates usage across supported platforms and presents it through interactive views that let users filter, sort, and explore trends without leaving the terminal. Tokscale also includes... -
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n8n-MCP
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor
n8n-mcp is a Model Context Protocol (MCP) server that turns the n8n workflow platform into a set of first-class, typed tools an AI assistant can understand and operate. It exposes structured knowledge of n8n nodes and operations so an agent can reason about workflows, parameters, and executions without scraping docs or guessing API shapes. The server focuses on making Claude Desktop (and other MCP-capable clients) “n8n-literate,” enabling tasks such as inspecting existing workflows,... -
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Trae Agent
LLM-based agent for general purpose software engineering tasks
Trae Agent is an open-source, LLM-based agent system also developed by ByteDance, focused primarily on automating software engineering workflows. It provides a command-line interface (CLI) that accepts natural-language instructions (e.g. “refactor this module,” “write a unit test,” “generate a REST API skeleton”), and then orchestrates tool-based workflows — such as file editing, shell/batch commands, code generation, code formatting or refactoring — to carry out complex engineering tasks. ... -
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Nimbalyst
Run multiple Codex and Claude Code AI sessions
Crystal is an open-source project focused on building a lightweight and flexible system for managing structured data, workflows, or automation pipelines, typically oriented toward developer productivity and extensible backend tooling. It is designed with modularity in mind, allowing developers to define reusable components and compose them into larger workflows that can adapt to different use cases. The project emphasizes simplicity and clarity, making it easier to understand and extend... -
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BotSharp
AI Multi-Agent Framework in .NET
Conversation as a platform (CaaP) is the future, so it's perfect that we're already offering the whole toolkits to our .NET developers using the BotSharp AI BOT Platform Builder to build a CaaP. It opens up as much learning power as possible for your own robots and precisely control every step of the AI processing pipeline. BotSharp is an open source machine learning framework for AI Bot platform builder. This project involves natural language understanding, computer vision and audio... -
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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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TypedAI
TypeScript AI platform with AI chat, Autonomous agents
...The platform also includes specialized software engineering agents that can assist with tasks such as code reviews or repository analysis. Developers can integrate multiple model providers and tools into the platform to create flexible agent pipelines. -
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Antigravity Claude Proxy
Proxy that exposes Antigravity provided claude / gemini models
...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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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters... -
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Bifrost
The Fastest LLM Gateway with built in OTel observability
...It abstracts away the complexity of working directly with multiple backend providers (OpenAI, Anthropic, AWS Bedrock, Google Vertex, etc.), enabling you to plug in providers and switch between them without touching your client code. It is built to be high performance: in benchmark tests at 5,000 requests per second, it reportedly adds only microseconds of overhead and achieves perfect success rates with no failed requests. Bifrost supports features such as automatic fallback (failover between providers), load balancing across API keys/providers, and semantic caching to reduce latency and cost. ... -
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OpenMonoAgent
Terminal-native coding agent powered by local LLMs
OpenMonoAgent.ai is a self-hosted coding agent designed to run entirely on the user’s own hardware. It pairs a .NET CLI with a local llama.cpp inference server so developers can use agentic coding workflows without cloud subscriptions or per-token billing. The project emphasizes privacy, local control, and ownership of the model, compute, and project data. It includes a terminal-native workflow, built-in tools, Docker sandboxing, and code intelligence features. The system can run on CPU or GPU and is designed to auto-configure itself when possible. ... -
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MCPHub
A unified hub for centralized management and dynamic organization
MCPHub is a unified hub that organizes many MCP servers behind clean Streamable HTTP (SSE) endpoints so clients can connect to “all tools,” a specific server, or logical groups. It’s designed to simplify multi-server operations: one process can multiplex several named STDIO servers and re-expose them over HTTP for IDEs and services. The README ships in multiple languages and includes deployment and routing guidance, signaling an intention to reach a broad user base. The project publishes to... -
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Determined
Determined, deep learning training platform
The fastest and easiest way to build deep learning models. Distributed training without changing your model code. Determined takes care of provisioning machines, networking, data loading, and fault tolerance. Build more accurate models faster with scalable hyperparameter search, seamlessly orchestrated by Determined. Use state-of-the-art algorithms and explore results with our hyperparameter search visualizations. -
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mergekit
Tools for merging pretrained large language models
...It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code. -
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vJEPA-2
PyTorch code and models for VJEPA2 self-supervised learning from video
VJEPA2 is a next-generation self-supervised learning framework for video that extends the “predict in representation space” idea from i-JEPA to the temporal domain. Instead of reconstructing pixels, it predicts the missing high-level embeddings of masked space-time regions using a context encoder and a slowly updated target encoder. This objective encourages the model to learn semantics, motion, and long-range structure without the shortcuts that pixel-level losses can invite. The... -
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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...