Search Results for "memory" - Page 3
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Showing 2490 open source projects for "memory"
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vLLM
A high-throughput and memory-efficient inference and serving engine
vLLM is a fast and easy-to-use library for LLM inference and serving. High-throughput serving with various decoding algorithms, including parallel sampling, beam search, and more. -
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Citron Neo
Research software designed to orchestrate virtual environments
Citron Neo is an advanced emulator project focused on replicating complex system environments with high performance and flexibility. It is designed to emulate modern console behavior while integrating improvements in CPU emulation, GPU rendering, and memory management. The project incorporates optimizations such as dynamic recompilation and Vulkan-based rendering to enhance performance across supported platforms. It also includes continuous updates that improve compatibility with games and system firmware, reflecting an active development cycle. Citron aims to provide a refined user experience through UI enhancements, faster loading times, and better resource handling. ... -
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Mochi Diffusion
Run Stable Diffusion on Mac natively
Run Stable Diffusion on Mac natively. This app uses Apple's Core ML Stable Diffusion implementation to achieve maximum performance and speed on Apple Silicon based Macs while reducing memory requirements. Extremely fast and memory efficient (~150MB with Neural Engine) Runs well on all Apple Silicon Macs by fully utilizing Neural Engine. Generate images locally and completely offline. Generate images based on an existing image (commonly known as Image2Image) Generated images are saved with prompt info inside EXIF metadata (view in Finder's Get Info window) Convert generated images to high resolution (using RealESRGAN) Autosave & restore images. ... -
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x-transformers
A simple but complete full-attention transformer
A simple but complete full-attention transformer with a set of promising experimental features from various papers. Proposes adding learned memory key/values prior to attending. They were able to remove feedforwards altogether and attain a similar performance to the original transformers. I have found that keeping the feedforwards and adding the memory key/values leads to even better performance. Proposes adding learned tokens, akin to CLS tokens, named memory tokens, that is passed through the attention layers alongside the input tokens. ... -
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EasyExcel
Lightweight Java library developed by Alibaba for reading and writing
EasyExcel is a Java library focused on reading and writing Excel files with very low memory usage, making it suitable for large datasets that overwhelm traditional APIs. It uses streaming/event-driven parsing to avoid loading entire workbooks into memory, and it maps rows to Java objects via simple annotations. Writers support multiple sheets, custom styles, merged cells, and template-based filling so production reports remain maintainable. -
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LangChain
⚡ Building applications with LLMs through composability ⚡
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
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Vellum
A personal AI assistant that evolves with you
Vellum is an open-source personal AI assistant platform designed to function as a persistent, autonomous digital companion across desktop and messaging environments. Unlike traditional chatbot interfaces, the project focuses on long-term memory, identity, proactive behavior, and real-world tool usage, enabling assistants to evolve alongside the user over time. The system integrates with macOS, Telegram, Slack, SMS, and additional communication channels while maintaining shared memory and context across platforms. Its architecture combines local-first storage, tool orchestration, sandboxed execution, and extensible workflow automation to allow assistants to read files, manage schedules, send messages, browse the web, and control applications. ... -
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Memori
SQL-native memory layer enabling persistent context for AI agents
Memori is an open source SQL-native memory engine designed to add persistent memory capabilities to AI applications, large language models, and multi-agent systems. It provides a memory layer that automatically captures conversations and interactions between users and AI models, allowing systems to retain knowledge across sessions instead of operating statelessly. It extracts structured information such as facts, preferences, rules, and summaries from interactions and stores them in standard SQL databases for later retrieval. ... -
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PHP7
PHP7 / Laravel Multi-format Streaming Parser
...DOM loading loads all the documents, making it easy to navigate and parse, and as such provides maximum flexibility for developers. Streaming implies iterating through the document, acts like a cursor, and stops at each element in its way, thus avoiding memory overkill. Thus, when it comes to big files, callbacks will be executed meanwhile file is downloading and will be much more efficient as far as memory is concerned. -
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Scalene
High-performance CPU, GPU, and memory profiler for Python
...Scalene separates out the percentage of memory consumed by Python code vs. native code. -
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Wandesk
Give intelligence shape. Let AI sculpt your desktop
...Built-in apps include Chat, Notebook, Ledger, Memory, Files, Tasks, Settings, Claude Code, Codex, and Open Source Radar. It is useful for users who want an AI workspace where apps, memory, and coding agents share context instead of living in separate chat threads. -
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ElasticMQ
In-memory message queue with an Amazon SQS-compatible interface
ElasticMQ is a lightweight, fully asynchronous, in-memory message queue implementation written in Scala / Akka. It provides a feature-compatible Amazon SQS REST API interface for testing, local development, or embedded usage. It can persist queues or run purely in-memory and also supports Docker deployment and a web UI. -
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QwenPaw
A personal AI assistant, easy to install
...QwenPaw emphasizes extensibility through modular components that developers can customize for research, personal assistants, automation systems, or enterprise AI workflows. The architecture integrates agent collaboration, planning systems, and long-term contextual memory to create more persistent and adaptive interactions. -
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FileTrees.jl
Parallel file processing made easy
...When computing lazy trees, these values are held in distributed memory and operated on in parallel. -
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Coverage.jl
Take Julia code coverage and memory allocation results, do useful thin
...This is useful for measuring how much of your code base your tests actually test, and can reveal the parts of your code that are not tested and might be hiding a bug. You can use Coverage.jl to summarize the results of this tracking or to send them to a service like Coveralls.io or Codecov.io. Julia can track how much memory is allocated by each line of your code. This can reveal problems like type instability, or operations that you might have thought were cheap (in terms of memory allocated) but aren't (i.e. accidental copying). -
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GlueSQL
GlueSQL is quite sticky. It attaches to anywhere
An embedded SQL database engine written in Rust, designed for lightweight, in-memory, and persistent storage use cases. -
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D++
C++ Discord API Bot Library - D++ is Lightweight and scalable
D++ is a lightweight and simple library for Discord written in modern C++. It is designed to cover as much of the API specification as possible and to have an incredibly small memory footprint, even when caching large amounts of data. It is created by the developer of TriviaBot and contributed to by a dedicated team of developers. -
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Infinispan
Infinispan is an open source data grid platform
Infinispan is a distributed in-memory data grid and caching system designed for high-performance computing. It allows applications to scale dynamically by distributing data across multiple nodes, reducing latency and improving resilience. -
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Supermemory
Memory engine and app that is extremely fast, scalable
...Users can interact with the system via conversational queries or traditional search interfaces, and the system leverages vector embeddings and memory scoring to prioritize the most relevant results. -
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Koila
Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code
Koila is a lightweight Python library designed to help developers avoid memory errors when training deep learning models with PyTorch. The library introduces a lazy evaluation mechanism that delays computation until it is actually required, allowing the framework to better estimate the memory requirements of a model before execution. By building a computational graph first and executing operations only when necessary, koila reduces the risk of running out of GPU memory during the forward pass of neural network training. ... -
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OpenAI Agents (Python)
A lightweight, powerful framework for multi-agent workflows
openai-agents-python is a library developed by OpenAI to simplify the process of creating and running agents that interact with tools and APIs using OpenAI models. It provides abstractions for tool usage, memory management, and agent workflows, enabling developers to define function-calling agents that reason through multi-step tasks. Ideal for building custom AI workflows, the library supports dynamic tool definitions and contextual memory handling. -
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DynamoRIO
Dynamic Instrumentation Tool Platform
DynamoRIO is a runtime code manipulation system that supports code transformations on any part of a program, while it executes. DynamoRIO exports an interface for building dynamic tools for a wide variety of uses: program analysis and understanding, profiling, instrumentation, optimization, translation, etc. Unlike many dynamic tool systems, DynamoRIO is not limited to insertion of callouts/trampolines and allows arbitrary modifications to application instructions via a powerful... -
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DataFrames.jl
In-memory tabular data in Julia
DataFrames.jl is a powerful Julia package for working with in-memory tabular data. It provides a familiar, flexible, and efficient interface for handling datasets, making it easy to load, manipulate, join, and analyze structured data. With syntax inspired by data frames in R and pandas in Python, it offers intuitive tools while taking advantage of Julia’s speed and type system. The package is actively maintained by the JuliaData community, with contributions from over 200 developers worldwide. ... -
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Claude Subconscious
Give Claude Code a subconscious
Claude Subconscious is an experimental plugin that enhances AI coding workflows by introducing a persistent “memory layer” for Claude Code through integration with Letta’s agent framework. It operates as a background agent that continuously observes user interactions, reads project files, and processes session transcripts to build long-term contextual memory. Unlike standard AI interactions that reset between sessions, this system accumulates knowledge over time, allowing it to recall user preferences, project structures, and recurring patterns across multiple sessions. ... -
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ZeroClaw
Fast, small, and fully autonomous AI assistant infrastructure
ZeroClaw is a Rust-native autonomous AI agent framework engineered for teams and developers who need highly efficient, secure, and modular AI automation infrastructure that can run reliably in both production and self-hosted environments. It is designed around a trait-based architecture so that model providers, communication channels, memory systems, and tooling integrations can be swapped or extended without rewriting core components, giving engineers flexibility and long-term maintainability. The framework features a compact single binary with fast cold and warm startup times and very low memory overhead, making it suitable even for resource-constrained hardware like small servers or edge devices. ...
