Showing 701 open source projects for "erp source code"

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    Gemini 3 and 200+ AI Models on One Platform

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  • 1
    Ploomber

    Ploomber

    The fastest way to build data pipelines

    Ploomber is an open-source framework designed to simplify the development and deployment of data science and machine learning pipelines. It allows developers to transform exploratory data analysis workflows into production-ready pipelines without rewriting large portions of code. The system integrates with common development environments such as Jupyter Notebook, VS Code, and PyCharm, enabling data scientists to continue working with familiar tools while building scalable workflows. ...
    Downloads: 0 This Week
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  • 2
    AIDE ML

    AIDE ML

    AI-Driven Exploration in the Space of Code

    AIDE ML is an open-source research framework designed to explore automated machine learning development through agent-based search and code optimization. The project implements the AIDE algorithm, which uses a tree-search strategy guided by large language models to iteratively generate, evaluate, and refine code. Instead of relying on manual experimentation, the agent autonomously drafts machine learning pipelines, debugs errors, and benchmarks performance against user-defined evaluation metrics. ...
    Downloads: 0 This Week
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  • 3
    CosyVoice

    CosyVoice

    Multi-lingual large voice generation model, providing inference

    CosyVoice is a multilingual large voice generation model that offers a full-stack solution for training, inference, and deployment of high-quality TTS systems. The model supports multiple languages, including Chinese, English, Japanese, Korean, and a range of Chinese dialects such as Cantonese, Sichuanese, Shanghainese, Tianjinese, and Wuhanese. It is designed for zero-shot voice cloning and cross-lingual or mix-lingual scenarios, so a single reference voice can be used to synthesize speech...
    Downloads: 3 This Week
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  • 4
    PyCaret

    PyCaret

    An open-source, low-code machine learning library in Python

    PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the experiment cycle exponentially and makes you more productive. In comparison with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only.
    Downloads: 0 This Week
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  • 5
    Genv

    Genv

    GPU environment management and cluster orchestration

    Genv is an open-source environment and cluster management system for GPUs. Genv lets you easily control, configure, monitor and enforce the GPU resources that you are using in a GPU machine or cluster. It is intended to ease up the process of GPU allocation for data scientists without code changes.
    Downloads: 3 This Week
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  • 6
    LTX-2

    LTX-2

    Python inference and LoRA trainer package for the LTX-2 audio–video

    ...The framework targets both interactive graphical applications and media-rich experiences, making it a solid foundation for games, creative tools, or visualization systems that demand both performance and flexibility. While being low-level, it also provides sensible defaults and helper abstractions that reduce boilerplate and help teams maintain clear, maintainable code.
    Downloads: 48 This Week
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  • 7
    Agently

    Agently

    AI Agent Application Development Framework

    Build AI agent native application in very little code. Easy to interact with AI agents in code using structure data and chained-calls syntax. Enhance AI Agent using plugins instead of rebuilding a whole new agent. Agently is a development framework that helps developers build AI agent native applications really fast. You can use and build AI agents in your code in an extremely simple way.
    Downloads: 0 This Week
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  • 8
    Unstract

    Unstract

    No-code LLM Platform to launch APIs and ETL Pipelines

    Unstract is a powerful open-source, no-code platform built to automate the extraction and structuring of unstructured documents using large language models and flexible workflows, enabling developers and data teams to turn messy files into organized JSON content without complex coding. It integrates a visual Prompt Studio environment where users can iteratively design extraction schemas, compare outputs from different models, and monitor costs and accuracy side by side, making it easier to refine prompts and extraction logic before deploying at scale. ...
    Downloads: 2 This Week
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  • 9
    LeWorldModel

    LeWorldModel

    Official code base for LeWorldModel: Stable End-to-End Joint-Embedding

    ...It provides automatic window tiling behavior, organizing application windows into structured layouts without requiring manual resizing or positioning. The project emphasizes a lightweight design, minimizing resource usage while maintaining responsiveness and stability. It is highly configurable through source code or configuration files, allowing users to tailor behavior, keybindings, and layouts to their preferences. le-wm is intended for users who prefer keyboard-driven workflows and a distraction-free desktop environment. Its architecture avoids unnecessary complexity, making it easy to understand, modify, and extend.
    Downloads: 4 This Week
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  • 10
    StarVector

    StarVector

    StarVector is a foundation model for SVG generation

    StarVector is a multimodal foundation model designed for generating Scalable Vector Graphics (SVG) from images or textual descriptions. The system treats vector graphics creation as a code generation problem, producing SVG code that can render detailed vector images. Its architecture combines computer vision techniques with language modeling capabilities so it can understand visual inputs and textual prompts simultaneously. The model converts raster images or text instructions into...
    Downloads: 0 This Week
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  • 11
    Continuous Claude v3

    Continuous Claude v3

    Context management for Claude Code. Hooks maintain state via ledgers

    Continuous Claude v3 is a persistent, multi-agent development environment built around the Claude Code CLI that aims to overcome the limitations of standard LLM context windows. Rather than relying on a single session’s context, Continuous Claude uses mechanisms like ledgers, YAML handoffs, and a memory system to preserve and recall state across multiple sessions, ensuring that learned insights and plans are not lost when context compaction occurs. The project orchestrates many specialized...
    Downloads: 1 This Week
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  • 12
    EasyOCR

    EasyOCR

    Ready-to-use OCR with 80+ supported languages

    Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc. EasyOCR is a python module for extracting text from image. It is a general OCR that can read both natural scene text and dense text in document. We are currently supporting 80+ languages and expanding. Second-generation models: multiple times smaller size, multiple times faster inference, additional characters and comparable accuracy to the first...
    Downloads: 42 This Week
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  • 13
    AutoMLOps

    AutoMLOps

    Build MLOps Pipelines in Minutes

    ...AutoMLOps can be configured to either use existing infra, or provision new infra, including source code repositories for versioning the generated MLOps codebase, build configs and triggers, artifact repositories for storing docker containers, storage buckets, etc.
    Downloads: 1 This Week
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  • 14
    E2B Cookbook

    E2B Cookbook

    Examples of using E2B

    E2B Cookbook is an open-source collection of example projects, guides, and reference implementations demonstrating how to build applications using the E2B platform. The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools.
    Downloads: 0 This Week
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  • 15
    CodeGen

    CodeGen

    Open-source model for program synthesis

    CodeGen is a family of open-source large language models designed specifically for program synthesis and code generation tasks. Developed by Salesforce Research, the models are trained on large datasets containing both natural language and programming language content. This allows them to translate natural language descriptions into functional code across a variety of programming languages.
    Downloads: 0 This Week
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  • 16
    ModelScope

    ModelScope

    Bring the notion of Model-as-a-Service to life

    ModelScope is built upon the notion of “Model-as-a-Service” (MaaS). It seeks to bring together most advanced machine learning models from the AI community, and streamlines the process of leveraging AI models in real-world applications. The core ModelScope library open-sourced in this repository provides the interfaces and implementations that allow developers to perform model inference, training and evaluation. In particular, with rich layers of API abstraction, the ModelScope library offers...
    Downloads: 9 This Week
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  • 17
    Spec Kit

    Spec Kit

    Toolkit to help you get started with Spec-Driven Development

    Spec Kit is an open-source toolkit designed to enable specification-driven development workflows powered by AI coding assistants. It introduces a structured process in which developers define detailed specifications first, then allow AI tools to generate plans, tasks, and implementation code aligned with those requirements. The toolkit provides scaffolding, prompt templates, and automation scripts that help teams maintain a clear source of truth throughout the development lifecycle. ...
    Downloads: 3 This Week
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  • 18
    CodiumAI Cover-Agent

    CodiumAI Cover-Agent

    CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation

    CodiumAI Cover Agent aims to help efficiently increasing code coverage, by automatically generating qualified tests to enhance existing test suites.
    Downloads: 1 This Week
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  • 19
    DeepWiki Open

    DeepWiki Open

    AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories

    DeepWiki Open is an open-source, AI-powered wiki generator that automatically creates fully navigable, richly structured wiki documentation for GitHub, GitLab, or Bitbucket repositories by combining code analysis, vector embeddings, retrieval-augmented generation (RAG), and visualization tools. Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and produce visual diagrams to help explain complex code structure. ...
    Downloads: 0 This Week
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  • 20
    PyGAD

    PyGAD

    Source code of PyGAD, Python 3 library for building genetic algorithms

    PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function.
    Downloads: 1 This Week
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  • 21
    Unsloth Studio

    Unsloth Studio

    Unified web UI for training and running open models locally

    Unsloth Studio is a web-based interface for running and training AI models locally with a unified and user-friendly experience. It allows users to work with a wide range of models for text, audio, vision, embeddings, and more without relying heavily on cloud infrastructure. Built on top of the Unsloth framework, it focuses on high-performance training with reduced VRAM usage and faster speeds compared to traditional methods. The platform supports fine-tuning, pretraining, and reinforcement...
    Downloads: 7 This Week
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  • 22
    ClearML

    ClearML

    Streamline your ML workflow

    ClearML is an open source platform that automates and simplifies developing and managing machine learning solutions for thousands of data science teams all over the world. It is designed as an end-to-end MLOps suite allowing you to focus on developing your ML code & automation, while ClearML ensures your work is reproducible and scalable. The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML powerful and versatile set of classes and methods. ...
    Downloads: 1 This Week
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  • 23
    HolyClaude

    HolyClaude

    AI coding workstation: Claude Code + web UI + 5 AI CLIs + headless

    HolyClaude is a developer-focused toolkit designed to enhance and extend the capabilities of Claude Code environments by providing structured prompts, utilities, and workflow enhancements for AI-assisted coding. The project centers around improving how developers interact with AI agents, enabling more efficient code generation, debugging, and task execution through optimized prompt engineering. It includes predefined templates and interaction patterns that guide the AI toward producing more...
    Downloads: 1 This Week
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  • 24
    ChatGPT Clone

    ChatGPT Clone

    ChatGPT interface with better UI

    ChatGPT Clone demonstrates a ChatGPT-style conversational interface wired to large-language-model backends, packaged so developers can self-host and extend. The goal is to replicate the core chat UX—message history, streaming tokens, code blocks, and system prompts—while letting you plug in different provider APIs or local models. It showcases a clean separation between the web client and the message orchestration layer so you can experiment with prompts, roles, and memory strategies. The...
    Downloads: 7 This Week
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  • 25
    Optax

    Optax

    Optax is a gradient processing and optimization library for JAX

    Optax is a gradient processing and optimization library for JAX. It is designed to facilitate research by providing building blocks that can be recombined in custom ways in order to optimize parametric models such as, but not limited to, deep neural networks. We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize...
    Downloads: 3 This Week
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