Search Results for "open world"
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Showing 9 open source projects for "open world"
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Obscura
The headless browser for AI agents and web scraping
Obscura is a security-focused project aimed at providing tools and techniques for enhancing privacy, anonymity, and operational security in digital environments. It is designed for users who need to obscure their digital footprint and reduce traceability across systems. The project typically includes utilities for masking identity, managing secure communication, and mitigating surveillance risks. It emphasizes practical implementations of privacy-preserving workflows rather than purely... -
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Utopia
World's first open-source enterprise world model
Utopia is an open-source enterprise world model designed to turn evolving organizational knowledge into a governed decision layer. It combines a bitemporal knowledge graph, editable ontology, retrieval, reasoning, and audit history in one self-hosted application. The system ingests documents and synchronized sources, then extracts entities and facts with provenance and validity intervals. -
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Every Code
Local AI coding agent CLI with multi-agent orchestration tools
Every Code (often referred to simply as Code) is a fast, local AI-powered coding agent designed to run directly in the terminal environment. It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with... -
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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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DeepProve
Framework to prove inference of ML models blazingly fast
DeepProve is an advanced cryptographic framework designed to verify machine learning model inference using zero-knowledge proofs, enabling trustless validation of AI computations without exposing underlying data. The project focuses on zkML, a rapidly emerging field that combines machine learning with zero-knowledge cryptography to ensure both privacy and correctness. It supports neural network architectures such as multilayer perceptrons and convolutional neural networks, allowing... -
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CodeGeeX4
CodeGeeX4-ALL-9B, a versatile model for all AI software development
CodeGeeX4 is the fourth-generation open source multilingual code large language model (LLM) developed by ZhipuAI. Designed as a powerful AI coding assistant, it supports over 100 programming languages and has been trained on a massive code and natural language corpus. Compared to its predecessors, CodeGeeX4 introduces improved reasoning, stronger alignment with developer needs, and better performance on real-world programming benchmarks. -
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Monoio
Rust async runtime based on io-uring
Monoio is a Rust asynchronous runtime designed for high-performance I/O-bound servers and applications, built around native OS async I/O primitives (e.g. io_uring on Linux, epoll / kqueue on other Unix-like systems), rather than layering atop an existing runtime. Its design philosophy centers on a “thread-per-core” model where each core runs its own event loop, minimizing cross-thread synchronization needs, avoiding the overhead and complexity of task scheduling, and letting developers write... -
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aigc
An e-book about the real-world application of LLM
"Building Large Language Model Applications: Application Development and Architecture Design" is an open source e-book about the real-world application of LLM. It introduces the basics and applications of large language models, as well as how to build your own models. These include writing, developing, and managing prompts, exploring what the best large language models can bring, and pattern and architecture design for LLM application development. -
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llm
An ecosystem of Rust libraries for working with large language models
llm is an ecosystem of Rust libraries for working with large language models - it's built on top of the fast, efficient GGML library for machine learning. The primary entry point for developers is the llm crate, which wraps the llm-base and the supported model crates. Documentation for the released version is available on Docs.rs. For end-users, there is a CLI application, llm-cli, which provides a convenient interface for interacting with supported models. Text generation can be done as a... -
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