Showing 2654 open source projects for "source-han"

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  • 1
    JamAI Base

    JamAI Base

    The collaborative spreadsheet for AI

    JamAI Base is an open-source backend platform designed to simplify the development of retrieval-augmented generation systems and AI-driven applications. The platform integrates both a relational database and a vector database into a single embedded architecture, allowing developers to store structured data alongside semantic embeddings. It includes built-in orchestration for large language models, vector search, and reranking pipelines so that AI applications can retrieve relevant information before generating responses. ...
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  • 2
    promptmap2

    promptmap2

    A security scanner for custom LLM applications

    ...The repository emphasizes broad coverage, including test rules for prompt stealing, jailbreaks, harmful content generation, hate-related outputs, social bias, and distraction attacks. It also supports multiple providers such as OpenAI, Anthropic, Google, xAI, and open-source models through Ollama, making it flexible for both commercial and local deployments.
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  • 3
    LOTUS

    LOTUS

    AI-Powered Data Processing: Use LOTUS to process all of your datasets

    LOTUS is an open-source framework and query engine designed to enable efficient processing of structured and unstructured datasets using large language models. The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis libraries. ...
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  • 4
    Pal

    Pal

    A personal context-agent that learns how you work

    Pal is an open-source AI personal agent built within the Agno ecosystem that functions as an intelligent digital assistant designed to learn from user activity over time. The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information.
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  • 5
    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. ...
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  • 6
    second-brain-ai-assistant-course

    second-brain-ai-assistant-course

    Learn to build your Second Brain AI assistant with LLMs

    The Second Brain AI Assistant Course is an open-source educational project designed to teach developers how to build a personal AI assistant that interacts with a user’s knowledge base. The course provides a structured curriculum that walks learners through the architecture and implementation of a production-ready AI system powered by large language models. The concept of a “second brain” refers to a personal knowledge repository containing notes, research, and documents that can be queried and analyzed using AI. ...
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  • 7
    Streamer-Sales

    Streamer-Sales

    LLM Large Model of Selling Anchor

    Streamer-Sales is an open-source large language model system designed specifically for e-commerce live streaming and automated product promotion. The project focuses on generating persuasive product descriptions and live presentation scripts that mimic the style of professional online sales hosts. By analyzing product characteristics and marketing information, the model can produce engaging explanations that emphasize benefits, features, and emotional appeal to encourage viewers to make purchasing decisions. ...
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  • 8
    NVIDIA Generative AI Examples

    NVIDIA Generative AI Examples

    Generative AI reference workflows

    NVIDIA GenerativeAIExamples is an open-source repository that provides practical reference implementations and example workflows for building generative AI applications using NVIDIA’s software ecosystem. The project is designed to help developers accelerate the development of AI applications by providing ready-to-run pipelines, notebooks, and tools that demonstrate how to integrate large language models into real-world systems.
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  • 9
    tiny-llm

    tiny-llm

    A course of learning LLM inference serving on Apple Silicon

    tiny-llm is an educational open-source project designed to teach system engineers how large language model inference and serving systems work by building them from scratch. The project is structured as a guided course that walks developers through the process of implementing the core components required to run a modern language model, including attention mechanisms, token generation, and optimization techniques.
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  • 10
    ERNIE

    ERNIE

    The official repository for ERNIE 4.5 and ERNIEKit

    ERNIE is an open-source large-model toolkit and model family from the PaddlePaddle ecosystem that focuses on training, fine-tuning, compression, and practical application of ERNIE large language models. The repository positions ERNIEKit as an industrial-grade development toolkit, emphasizing end-to-end workflows that span high-performance pre-training, supervised fine-tuning, and alignment.
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  • 11
    Modular Platform

    Modular Platform

    The Modular Platform (includes MAX & Mojo)

    Modular is a high-performance AI infrastructure company repository focused on building next-generation compute and software tools for machine learning workloads. The project centers on enabling developers to run AI models faster and more efficiently by rethinking the traditional ML software stack. It is closely associated with the Mojo programming language and related tooling that aims to combine Python usability with systems-level performance. Modular’s ecosystem is designed to simplify...
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  • 12
    Aden Hive

    Aden Hive

    Outcome driven agent development framework that evolves

    Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes.
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  • 13
    Fara-7B

    Fara-7B

    An Efficient Agentic Model for Computer Use

    Fara-7B is a Microsoft initiative aimed at bringing rigor, transparency, and structured evaluation to AI systems through automated and customizable assessment frameworks. It provides stakeholders with a way to benchmark and evaluate models across dimensions such as fairness, robustness, security, privacy, and ethical considerations. Rather than relying on ad-hoc or manual review processes, FARA enables organizations to profile AI behavior using standardized tests, metrics, and reporting...
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  • 14
    InfiAgent

    InfiAgent

    Build your own Cowork, AI Scientist and other SoTA Agents

    infiAgent is an open-source AI agent framework for building powerful, long-running autonomous agents capable of tackling complex tasks without collapsing under growing context or tool invocation histories. Designed as a “Multi-Level Agent” (MLA) system, it externalizes persistent state to the file system so that agents can operate over unlimited runtime without the need for token-intensive context compression, enabling workflows such as research paper drafting, experiments, coding, and document generation to run reliably. ...
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  • 15
    IQuest-Coder-V1 Model Family

    IQuest-Coder-V1 Model Family

    New family of code large language models (LLMs)

    IQuest-Coder-V1 is a cutting-edge family of open-source large language models specifically engineered for code generation, deep code understanding, and autonomous software engineering tasks. These models range from tens of billions to smaller footprints and are trained on a novel code-flow multi-stage paradigm that captures how real software evolves over time — not just static code snapshots — giving them a deeper semantic understanding of programming logic.
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  • 16
    Universal Commerce Protocol (UCP)

    Universal Commerce Protocol (UCP)

    The common language for platforms, agents and businesses.

    Universal Commerce Protocol (UCP) is an open standard designed to unify how platforms, businesses, and payment providers interact across the modern commerce ecosystem. It provides a common language that eliminates fragmented, custom integrations and enables seamless interoperability between diverse commerce systems. Built for an increasingly agentic web, UCP supports AI-driven platforms that can discover products, manage carts, and complete transactions securely on a user’s behalf. Its...
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  • 17
    MAI-UI

    MAI-UI

    Real-World Centric Foundation GUI Agents

    MAI-UI is a cutting-edge open-source project that implements a family of foundation GUI (Graphical User Interface) agent models capable of interpreting natural language and performing real-world GUI navigation and control tasks across mobile and desktop environments. Developed by Tongyi-MAI (Alibaba’s research initiative), the MAI-UI models are multimodal agents trained to understand user instructions and corresponding screenshots, grounding those instructions to on-screen elements and generating sequences of GUI actions such as taps, swipes, text input, and system commands. ...
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  • 18
    USO

    USO

    Open-sourced unified customization model

    USO is ByteDance’s “Unified Style and Subject-Driven Generation” framework, open-sourced to allow customization in generative modeling by disentangling style and subject representation and using reward learning to guide generation. The system is designed such that users can control both “what” is generated (the subject: e.g. a person, object, scene) and “how” it is generated (the style: artistic style, color palette, aesthetic) separately, giving much more flexibility than conventional...
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  • 19
    ESPnet

    ESPnet

    End-to-end speech processing toolkit

    ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. This combination allows researchers to leverage modern neural architectures while...
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  • 20
    Meta-World

    Meta-World

    Collections of robotics environments

    Meta-World is an open-source benchmark suite of robotic manipulation environments focused on multi-task and meta reinforcement learning. It provides a large collection of continuous-control tasks, such as reaching, pushing, opening doors, and manipulating objects with a simulated robot arm. The library defines standardized benchmarks like MT1, MT10, and MT50 for multi-task learning, where a single policy is trained across different numbers of tasks.
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  • 21
    Agentex

    Agentex

    Open source codebase for Scale Agentex

    AgentEX is an open framework from Scale for building, running, and evaluating agentic workflows, with an emphasis on reproducibility and measurable outcomes rather than ad-hoc demos. It treats an “agent” as a composition of a policy (the LLM), tools, memory, and an execution runtime so you can test the whole loop, not just prompting. The repo focuses on structured experiments: standardized tasks, canonical tool interfaces, and logs that make it possible to compare models, prompts, and tool...
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  • 22
    Inspect Petri

    Inspect Petri

    An alignment auditing agent capable of exploring alignment hypothesis

    Inspect Petri is an open-source alignment auditing agent that lets researchers rapidly test concrete safety hypotheses against target models using realistic, multi-turn scenarios. Instead of building bespoke evals, Inspect Petri automatically generates audit environments from seed “special instructions,” orchestrates an auditor model to probe a target model, and simulates tool use and rollbacks to surface risky behaviors.
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  • 23
    GLM-V

    GLM-V

    GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning

    GLM-V is an open-source vision-language model (VLM) series from ZhipuAI that extends the GLM foundation models into multimodal reasoning and perception. The repository provides both GLM-4.5V and GLM-4.1V models, designed to advance beyond basic perception toward higher-level reasoning, long-context understanding, and agent-based applications. GLM-4.5V builds on the flagship GLM-4.5-Air foundation (106B parameters, 12B active), achieving state-of-the-art results on 42 benchmarks across image, video, document, GUI, and grounding tasks. ...
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  • 24
    VectorizedMultiAgentSimulator (VMAS)

    VectorizedMultiAgentSimulator (VMAS)

    VMAS is a vectorized differentiable simulator

    VectorizedMultiAgentSimulator is a high-performance, vectorized simulator for multi-agent systems, focusing on large-scale agent interactions in shared environments. It is designed for research in multi-agent reinforcement learning, robotics, and autonomous systems where thousands of agents need to be simulated efficiently.
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  • 25
    Adapters

    Adapters

    A Unified Library for Parameter-Efficient Learning

    Adapters is an add-on library to HuggingFace's Transformers, integrating 10+ adapter methods into 20+ state-of-the-art Transformer models with minimal coding overhead for training and inference. Adapters provide a unified interface for efficient fine-tuning and modular transfer learning, supporting a myriad of features like full-precision or quantized training (e.g. Q-LoRA, Q-Bottleneck Adapters, or Q-PrefixTuning), adapter merging via task arithmetics or the composition of multiple adapters...
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