Showing 769 open source projects for "process"

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  • 1
    WFGY 3.0

    WFGY 3.0

    A tension reasoning engine over 131 S-class problems

    ...The project introduces a conceptual reasoning engine that analyzes complex problems by identifying semantic compression errors and residual assumptions within a system’s reasoning process. Its architecture treats reasoning failures as measurable signals that can be detected and analyzed rather than simply observed as incorrect answers. Different versions of the framework, including WFGY 1.0, 2.0, and 3.0, represent stages of development where early conceptual ideas evolved into more structured reasoning engines and diagnostic tools. ...
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  • 2
    Agentic Context Engine

    Agentic Context Engine

    Make your agents learn from experience

    ...Instead of relying solely on model training or fine-tuning, the framework focuses on structured context engineering, allowing agents to accumulate knowledge from past successes and failures during task execution. The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and curation, enabling agents to refine strategies across repeated tasks. In this workflow, one component generates solutions, another reflects on outcomes, and a third curates useful knowledge so it can be reused in future interactions. This architecture allows agents to gradually build persistent operational memory without requiring additional training datasets or model retraining.
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  • 3
    LISA

    LISA

    LISA: Reasoning Segmentation via Large Language Model

    ...This approach allows the system to identify objects or regions in images based on semantic descriptions, contextual reasoning, and world knowledge. The model integrates multimodal capabilities by combining language understanding with visual perception so that text instructions guide the segmentation process. Researchers created a specialized task called reasoning segmentation, where the model must generate a mask for regions described in natural language instructions.
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  • 4
    FastDeploy

    FastDeploy

    High-performance Inference and Deployment Toolkit for LLMs and VLMs

    FastDeploy is an open-source inference and deployment toolkit designed to simplify the process of running and serving deep learning models across a wide range of hardware platforms. Developed within the PaddlePaddle ecosystem, the toolkit focuses on providing high-performance deployment capabilities for modern AI models including large language models and vision-language systems. The platform enables developers to deploy trained models quickly using optimized inference pipelines that support GPUs, specialized AI accelerators, and other hardware architectures. ...
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  • 5
    Agents 2.0

    Agents 2.0

    An Open-source Framework for Data-centric Language Agents

    ...The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During training, the system performs a forward execution where the agent completes a task and records the trajectory of prompts, outputs, and tool usage. A prompt-based loss function is then applied to evaluate the quality of the outcome, generating language-based gradients that guide improvements to the agent pipeline.
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  • 6
    zpdf

    zpdf

    Zero-copy PDF text extraction library written in Zig

    ...It leans heavily on memory-mapped file reading and zero-copy patterns where possible, so it can scan large PDFs without repeatedly copying data around in memory. The library supports streaming extraction using efficient arena allocation, making it well suited for workloads that need to process big documents quickly or in batches. It implements multiple PDF decompression filters and handles common font encoding pathways, which are essential for turning raw PDF content streams into readable text. It also understands both classic cross-reference tables and newer cross-reference streams, including PDF 1.5+ features, and it offers configurable strict vs permissive error handling depending on whether you prioritize correctness or robustness.
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  • 7
    FinRobot

    FinRobot

    An Open-Source AI Agent Platform for Financial Analysis using LLMs

    FinRobot is an open-source AI framework focused on automating financial data workflows by combining data ingestion, feature engineering, model training, and automated decision-making pipelines tailored for quantitative finance applications. It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to measure strategy performance. Built with modularity in mind, FinRobot allows users to plug in custom models — from classical algorithms to deep learning architectures — and orchestrate components in pipelines that can run reproducibly across experiments. ...
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  • 8
    Ring

    Ring

    Ring is a reasoning MoE LLM provided and open-sourced by InclusionAI

    ...Efficient architecture and memory design for large-scale reasoning. If you are located in mainland China, we also provide the model on ModelScope.cn to speed up the download process.
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  • 9
    Cobbler

    Cobbler

    Cobbler is a versatile Linux deployment server

    ...Automation is the key to speed, consistency and repeatability. These properties are critical to managing infrastructure, whether it is comprised of a few servers or a few thousand servers. Cobbler helps by automating the process of provisioning servers from bare metal, or when deploying virtual machines onto various hypervisors. Just as configuration management systems rely on templates to simplify updates, so too does Cobbler.
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  • 10
    DeepAudit

    DeepAudit

    AI multi-agent platform for automated code security auditing system

    DeepAudit is an open source code security auditing platform that uses a multi-agent architecture to analyze and identify vulnerabilities in software projects. Instead of relying solely on traditional static analysis, it simulates the reasoning process of security experts through coordinated agents responsible for orchestration, reconnaissance, analysis, and verification. DeepAudit performs deep semantic understanding of code, enabling it to detect complex vulnerabilities that span multiple files and business logic layers. It also includes automated proof-of-concept validation using a sandboxed environment, allowing detected issues to be tested for real exploitability. ...
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  • 11
    hCaptcha Challenger

    hCaptcha Challenger

    Gracefully face hCaptcha challenge with multimodal llms

    hCaptcha Challenger is an open-source automation framework designed to solve hCaptcha verification challenges using computer vision models and multimodal reasoning techniques. The project integrates machine learning models capable of analyzing visual captcha tasks and identifying the correct responses required to pass the verification process. Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks that can classify images, detect objects, and interpret spatial relationships. The framework includes support for multiple types of captcha challenges such as object selection, drag-and-drop puzzles, and image labeling tasks. ...
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  • 12
    IVRE

    IVRE

    Open source framework for large scale network reconnaissance and analy

    IVRE is an open source network reconnaissance framework designed to collect, process, and analyze intelligence gathered from network scans and traffic data. It provides tools for both active and passive reconnaissance, enabling users to understand how networks behave and identify exposed services or infrastructure. The framework integrates with well known security and scanning tools such as Nmap, Masscan, ZGrab2, ZDNS, and Zeek to gather large amounts of network intelligence.
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  • 13
    mergekit

    mergekit

    Tools for merging pretrained large language models

    ...This approach allows researchers to combine specialized models into a more versatile system capable of performing multiple tasks. mergekit implements a variety of merging algorithms and strategies that control how model parameters are blended together during the merging process. The library is designed to operate efficiently even in environments with limited hardware resources by using memory-efficient processing methods that can run entirely on CPUs. It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code.
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  • 14
    Every Door

    Every Door

    A dedicated app for collecting thousands of POI for OpenStreetMap

    ...Just go to a mall, and start Every Door. You'll see mapped shops around you: tap on the checkmark for any that are still there, and add shops that are not on the map. That's the entire process: you can keep your entire town up-to-date thanks to this simple editor. There is also a micromapping mode for verifying and adding benches and street lamps. And an entrance mode for adding building attributes and entrances, which are merged automatically into building contours.
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  • 15
    Xorbits Inference

    Xorbits Inference

    Replace OpenAI GPT with another LLM in your app

    Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop. Xorbits Inference(Xinference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. With Xorbits...
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  • 16
    MegaLinter

    MegaLinter

    Mega-Linter analyzes 50 languages, 22 formats, 21 tooling formats etc.

    ...By using code formatters and code linters, you ensure that your code base is easier to read and respects best practices, from the kick-off to each step of the project lifecycle. Not all developers have the good habit to use linters in their IDEs, making code reviews harder and longer to process.
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  • 17
    Segmentation Models

    Segmentation Models

    Segmentation models with pretrained backbones. PyTorch

    ...Pytorch Image Models (a.k.a. timm) has a lot of pretrained models and interface which allows using these models as encoders in smp, however, not all models are supported. Input channels parameter allows you to create models, which process tensors with an arbitrary number of channels.
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  • 18
    Archivematica

    Archivematica

    Free and open-source digital preservation system

    ...Archivematica is an open-source application based on recognized standards that makes it possible to preserve long-term access to your institution's digital content. Archivematica is a set of free software tools that allow the user to process digital objects from the moment they are entered into the system until their publication according to the ISO-OAIS functional model. The user can monitor and control the ingestion and preservation of micro-services through the control panel. Archivematica uses standards such as METS, PREMIS, Dublin Core, and the BagIt specification.
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  • 19
    Key-book

    Key-book

    Proofs, cases, concept supplements, and reference explanations

    The book "Introduction to Machine Learning Theory" (hereinafter referred to as "Introduction") written by Zhou Zhihua, Wang Wei, Gao Wei, and other teachers fills the regret of the lack of introductory works on machine learning theory in China. This book attempts to provide an introductory guide for readers interested in learning machine learning theory and researching machine learning theory in an easy-to-understand language. "Guide" mainly covers seven parts, corresponding to seven...
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  • 20
    Petastorm

    Petastorm

    Petastorm library enables single machine or distributed training

    Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular...
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  • 21
    Triton Inference Server

    Triton Inference Server

    The Triton Inference Server provides an optimized cloud

    ...HTTP/REST and GRPC inference protocols based on the community-developed KServe protocol. A C API and Java API allow Triton to link directly into your application for edge and other in-process use cases.
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  • 22
    Super-Linter

    Super-Linter

    Combination of multiple linters to install as a GitHub Action

    This repository is for the GitHub Action to run a Super-Linter. It is a simple combination of various linters, written in bash, to help validate your source code. The super-linter finds issues and reports them to the console output. Fixes are suggested in the console output but not automatically fixed, and a status check will show up as failed on the pull request. The design of the Super-Linter is currently to allow linting to occur in GitHub Actions as a part of continuous integration...
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  • 23
    Open Vision Agents by Stream

    Open Vision Agents by Stream

    Build Vision Agents quickly with any model or video provider

    Open Vision Agents by Stream is an open source framework from Stream for building real time, multimodal AI agents that watch, listen, and respond to live video streams. It focuses on combining video understanding models, such as YOLO and Roboflow based detectors, with real time large language models like OpenAI Realtime and Gemini Live to create interactive experiences. The framework uses Stream’s ultra low latency edge network so agents can join sessions quickly and maintain very low audio...
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  • 24
    Qwen-Agent

    Qwen-Agent

    Agent framework and applications built upon Qwen>=3.0

    Qwen-Agent is a framework for building applications / agents using Qwen models (version 3.0+). It provides components for instruction following, tool usage (function calling), planning, memory, RAG (retrieval augmented generation), code interpreter, etc. It ships with example applications (Browser Assistant, Code Interpreter, Custom Assistant), supports GUI front-ends, backends, server setups. Agent workflow can maintain context / memory to perform multi-turn or more complex logic over time....
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  • 25
    EduCDM

    EduCDM

    The Model Zoo of cognitive diagnosis models

    The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM), Item Response Ranking framework (IRR), Incremental Cognitive Diagnosis (ICD) and Knowledge-association baesd extension of NeuralCD (KaNCD). Cognitive diagnosis model (CDM) for intelligent educational systems...
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