Search Results for "software without code" - Page 11
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Showing 714 open source projects for "software without code"
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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... -
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Trail of Bits Skills Marketplace
Trail of Bits Claude Code skills for security research, vulnerability
Trail of Bits Skills Marketplace is a specialized Claude Code skills marketplace built by the security research firm Trail of Bits that focuses on enhancing AI-assisted workflows for vulnerability discovery, testing, and secure development. The repository groups a set of plug-in skills tailored toward static analysis, code auditing, secure defaults detection, and other practices that matter in software security. -
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H2O LLM Studio
Framework and no-code GUI for fine-tuning LLMs
Welcome to H2O LLM Studio, a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). You can also use H2O LLM Studio with the command line interface (CLI) and specify the configuration file that contains all the experiment parameters. To finetune using H2O LLM Studio with CLI, activate the pipenv environment by running make shell. With H2O LLM Studio, training your large language model is easy and intuitive. First, upload your dataset and then start... -
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files-to-prompt
Concatenate a directory full of files into a single prompt
...It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It includes rich filtering controls, letting you limit by extension, include or skip hidden files, and ignore paths that match glob patterns or .gitignore rules. The output format is flexible: you can emit plain text, Markdown with fenced code blocks, or a Claude-XML style format designed for structured multi-file prompts. ... -
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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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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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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and... -
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best... -
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Auto Claude
Autonomous multi-session AI coding
Auto-Claude is an autonomous, multi-agent coding framework that organizes software work into a structured workflow where agents plan, build, and validate code with minimal manual micromanagement. Instead of relying on a single chat thread to do everything, it uses coordinated agents and a task-driven approach so multiple steps—like investigation, implementation, and testing—can be executed systematically. The project aims to make “agentic software engineering” feel like running a small virtual dev team by giving you an opinionated process for turning goals into scoped tasks and then driving those tasks to completion. ... -
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Papermerge
Open Source Document Management System for Digital Archives
...Store, organize and index scanned documents in PDF, JPEG and TIFF formats. Instantly find relevant information using full text, tags and metadata-based search. Papermerge is free and open-source software which means that transparency is the core value of our software development. Source code can be reviewed and improved by anyone from anywhere. Papermerge supports multiple users. Each user can be assigned different permissions to perform only a specific kind of action e.g. view only documents from a specific folder. OCR technology is vital part of Papermerge. ... -
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Bolt.new
Prompt, run, edit, and deploy full-stack web applications
...Bolt.new is designed to significantly lower the barrier to entry for software creation, making it accessible not only to developers but also to product managers, designers, and non-technical users who want to quickly prototype or launch applications. -
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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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Kubeflow pipelines
Machine Learning Pipelines for Kubeflow
Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. A pipeline is a description of an ML workflow, including all of the components in the workflow and how they combine in the form of a graph. The pipeline includes the definition of the inputs (parameters) required to run the pipeline and the inputs and outputs of each component. A pipeline component is a self-contained set of user code, packaged as... -
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cuML
RAPIDS Machine Learning Library
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU equivalents. For details on performance, see the cuML Benchmarks Notebook. -
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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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Neuron AI
The PHP Agentic Framework to build production-ready AI driven apps
Neuron AI is a PHP agentic framework for building production-ready AI applications that connect models, memory, vector databases, and tools into working agents. It is designed for developers who want to create systems such as RAG pipelines, multi-agent workflows, and business process automations without having to hand-build every integration from scratch. The framework provides an Agent class that can be extended to inherit core capabilities like memory, tools, function calling, and retrieval-augmented generation. Its design is modular, so developers can swap model providers with minimal changes to their application code, which makes it practical for teams that need flexibility across vendors. ... -
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Kong Konnect MCP
A Model Context Protocol server for interacting with Kong Konnect
...By bridging MCP clients to Kong’s control plane, the project allows autonomous agents to retrieve data on traffic metrics, route definitions, services, plugins, and consumer settings without writing custom API integration code. It also groups tools into categories—such as analytics, configuration, and control plane management—to organize capabilities logically for AI workflows. -
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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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aisuite
Simple, unified interface to multiple Generative AI providers
...Using an interface similar to OpenAI's, aisuite makes it easy to interact with the most popular LLMs and compare the results. It is a thin wrapper around Python client libraries and allows creators to seamlessly swap out and test responses from different LLM providers without changing their code. Today, the library is primarily focused on chat completions. We will expand it to cover more use cases in the near future. Currently supported providers are - OpenAI, Anthropic, Azure, Google, AWS, Groq, Mistral, HuggingFace and Ollama. To maximize stability, aisuite uses either the HTTP endpoint or the SDK for making calls to the provider. -
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Stable Baselines3
PyTorch version of Stable Baselines
Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch. It is the next major version of Stable Baselines. You can read a detailed presentation of Stable Baselines3 in the v1.0 blog post or our JMLR paper. These algorithms will make it easier for the research community and industry to replicate, refine, and identify new ideas, and will create good baselines to build projects on top of. We expect these tools will be used as a base around... -
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AI Runner
Offline inference engine for art, real-time voice conversations
...It is implemented as a desktop-oriented Python application and emphasizes privacy and self-hosting, allowing users to work with text-to-speech, speech-to-text, text-to-image and multimodal models without sending data to external services. At the core of its LLM stack is a mode-based architecture with specialized “modes” such as Author, Code, Research, QA and General, and a workflow manager that automatically routes user requests to the right agent based on the task. The project has a strong focus on developer ergonomics, with thorough development guidelines, environment configuration using .env variables, and a clear structure for tests, tools and agents.