Search Results for "memory"
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Showing 24 open source projects for "memory"
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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. ... -
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OpenHuman
Your Personal AI super intelligence. Private, simple and powerful
...It focuses on a private, desktop-first experience with a friendly interface, onboarding flows, and a persistent assistant that can remember context over time. The project connects to common productivity tools, gathers fresh information from integrations, and organizes user knowledge into a local memory system. It also includes practical agent tools such as web search, web fetching, file access, coding utilities, voice input, text-to-speech, and model routing. Its goal is to make an AI assistant feel continuously useful across meetings, messages, documents, tasks, and personal workflows. Since it is still in early beta, it is best suited for technical users and early adopters who want to experiment with a customizable personal AI environment. -
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Moltis
A Rust-native claw you can trust
...The platform also includes long-term memory powered by hybrid vector and full-text search, allowing the assistant to retain context across sessions. With multi-channel access such as web UI, Telegram, and API endpoints, Moltis functions as a unified automation hub intended for developers and advanced users who want full control. -
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Claw Code
AI agent harness for AI coding agents
...It emphasizes harness engineering—how agents are structured, how they interact with tools, and how they maintain context during execution. The system is being actively expanded, with a Rust-based runtime in development to improve performance and memory safety. Overall, Claw Code serves as a research-driven platform for advancing agent-based software development systems. -
Compliant and Reliable File Transfers Backed by Top Security CertificationsStop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
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llmfit
157 models, 30 providers, one command to find what runs on hardware
llmfit is a terminal-based utility that helps developers determine which large language models can realistically run on their local hardware by analyzing system resources and model requirements. The tool automatically detects CPU, RAM, GPU, and VRAM specifications, then ranks available models based on performance factors such as speed, quality, and memory fit. It provides both an interactive terminal user interface and a traditional CLI mode, enabling flexible workflows for different user preferences. llmfit also supports advanced configurations including multi-GPU setups, mixture-of-experts architectures, and dynamic quantization recommendations. By presenting clear performance estimates and compatibility guidance, the project reduces the trial-and-error typically involved in local LLM experimentation. ... -
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Lightpanda Browser
Lightpanda: the headless browser designed for AI and automation
...The browser is implemented using the Zig programming language and integrates the V8 JavaScript engine to run modern web applications and scripts efficiently. Because it avoids graphical rendering and other heavy browser components, the system uses significantly less memory and launches almost instantly compared to conventional browsers such as Chrome. -
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uzu
A high-performance inference engine for AI models
...The engine implements a hybrid architecture in which model layers can be executed either as custom GPU kernels or through Apple’s MPSGraph API, allowing it to balance performance and compatibility depending on the workload. By utilizing Apple’s unified memory architecture, uzu reduces memory copying overhead and improves inference throughput for local AI workloads. The system includes a simple high-level API that enables developers to run models, create inference sessions, and generate outputs with minimal configuration. -
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Crabtalk
Agents daemon that hides nothing
...It is implemented in Rust and focuses on delivering high performance, reliability, and low overhead compared to more complex agent frameworks. The system is built around a small set of core primitives, including skills, memory, context isolation, and extensions, which together enable flexible and modular agent behavior. CrabTalk emphasizes simplicity by avoiding unnecessary abstractions, allowing developers to maintain full control over how agents operate and interact with their environment. One of its key design goals is to address common issues in multi-agent systems, such as context fragmentation and coordination inefficiencies, by providing clearer structure and tighter control over execution. -
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LangChain Rust
LangChain for Rust, the easiest way to write LLM-based programs
...The library aims to provide Rust developers with a structured framework for orchestrating prompts, chains, agents, and external tools within LLM-driven workflows. By adapting LangChain concepts to the Rust programming language, the project emphasizes performance, safety, and efficient memory management. Developers can use the framework to build chatbots, autonomous agents, and knowledge-augmented AI systems that interact with external data sources. The library provides abstractions for model providers, prompt templates, conversation memory, and vector search integrations. It also enables the construction of multi-step pipelines where LLM outputs feed into subsequent actions or tool calls. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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IronClaw
IronClaw is OpenClaw inspired but focused on privacy & security
...IronClaw runs untrusted tools inside isolated WebAssembly (WASM) sandboxes with strict capability-based permissions. It supports multiple interaction channels, including REPL, HTTP webhooks, Telegram, Slack, and a real-time web gateway. With dynamic tool building, persistent memory, and background automation, IronClaw is built to securely expand and adapt to your personal and professional workflows. -
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forkd
Fork() for AI agent microVMs
...Instead of cold-booting a separate virtual machine for every worker, it forks children from a warmed parent snapshot and uses copy-on-write behavior to share the initial memory state. This makes it useful for spawning many isolated agent environments quickly during parallel research, testing, or code execution. The project is focused on runtime performance, sandbox isolation, and efficient branching from a live or prepared VM state. It is especially relevant for developers building agent infrastructure where many short-lived execution branches need to run safely. forkd is best understood as a low-level systems tool for scalable, isolated AI-agent workloads. -
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Spice.ai OSS
A self-hostable CDN for databases
...Spice makes it easy and fast to query data from one or more sources using SQL. You can co-locate a managed dataset with your application or machine learning model, and accelerate it with Arrow in-memory, SQLite/DuckDB, or with attached PostgreSQL for fast, high-concurrency, low-latency queries. Accelerated engines give you flexibility and control over query cost and performance. -
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OpenFang
Open-source Agent Operating System
...Written primarily in Rust, the project focuses on building a high-performance runtime where multiple specialized agents can collaborate to complete complex computational or development tasks. It aims to move beyond simple chat-based agents by providing infrastructure for persistent agent memory, task coordination, and scalable execution. The system is positioned as a foundation for building advanced AI tooling, particularly in environments that require tight integration with GPU workflows and modern AI pipelines. OpenFang emphasizes modularity and extensibility so developers can plug in custom agents, tools, or execution backends. ... -
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Burn
Burn is a new comprehensive dynamic Deep Learning Framework
Burn is a new comprehensive dynamic Deep Learning Framework from Tracel AI built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. Burn emphasizes performance, flexibility, and portability for both training and inference. Developed in Rust, it is designed to empower machine learning engineers and researchers across industry and academia. -
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Sail
A drop-in Apache Spark replacement written in Rust
Sail is an open-source distributed computation framework designed to unify batch processing, stream processing, and AI workloads into a single, high-performance engine. It is built entirely in Rust, eliminating JVM overhead and enabling predictable performance, fast startup times, and improved memory safety compared to traditional big data frameworks. Sail is compatible with the Spark Connect protocol, which means existing Spark SQL and DataFrame workloads can run without code changes, making adoption seamless for teams already using Spark-based pipelines. The framework is designed to operate across a variety of environments, including local machines, Kubernetes clusters, and cloud deployments, allowing flexible scaling based on workload requirements. ... -
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pgvecto.rs
Vector database plugin for Postgres, written in Rust
pgvecto.rs is a Postgres extension that provides vector similarity search functions. It is written in Rust and based on pgrx. It is currently under heavy development, please take care when using it in production. pgvecto.rs is a Postgres extension, which means that you can use it directly within your existing database. This makes it easy to integrate into your existing workflows and applications. pgvecto.rs supports filtering. You can set conditions when searching or retrieving points. This... -
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Plano
Delivery infrastructure for agentic apps
...Built on modern proxy technology and compatible with any language or AI framework, Plano enables developers to focus on core agent logic instead of infrastructure complexity. The system provides intelligent LLM routing APIs that support model agility, along with filter chains for safety, moderation, and memory hooks. It also exposes rich traces, metrics, and logs to support continuous improvement of agent behavior in production. Overall, Plano functions as delivery infrastructure for scalable, maintainable AI agent systems. -
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shimmy
Python-free Rust inference server
...This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture intact. Shimmy focuses on performance and simplicity, using efficient runtime components to minimize memory usage and startup time compared to heavier inference frameworks. It supports modern model formats such as GGUF and SafeTensors and can automatically discover models stored locally or in common directories used by other AI tools. Advanced capabilities include CPU offloading for Mixture-of-Experts models and GPU acceleration, enabling large models to run on consumer hardware with limited VRAM. -
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Extractous
Fast and efficient unstructured data extraction
...Its purpose is to extract text and metadata efficiently from formats such as PDF, Word, HTML, email archives, images, and more, without depending on external APIs or separate parsing servers. The project emphasizes performance and low memory usage, and its maintainers describe it as a local-first alternative to heavier extraction stacks. For broader format support, the system combines its Rust core with ahead-of-time compiled Apache Tika shared libraries, which allows it to extend parsing coverage while still avoiding traditional server-based overhead. It also supports OCR for images and scanned documents through Tesseract, making it useful for document ingestion pipelines that include image-based or scanned inputs. -
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rust-bert
Rust native ready-to-use NLP pipelines and transformer-based models
...The project ports many capabilities of the Hugging Face Transformers ecosystem into the Rust programming language. It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory efficiency. The library integrates with Rust machine learning infrastructure using crates such as tch-rs and ONNX Runtime for model execution. It also includes tokenization utilities, model architectures, and task-specific pipelines that simplify the development of NLP applications. Because Rust is known for its safety and performance, this project enables developers to deploy modern NLP models in production systems written in Rust. -
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OpenChat for Linux
OpenChat for Linux — a fast, lightweight desktop client for ChatGPT
OpenChat for Linux is a desktop client for ChatGPT / OpenAI Chat designed specifically for Linux. It’s built with Tauri (Rust) for low resource usage and stability, and it uses a “message window” approach (keeps a small active slice of the conversation and loads more as you scroll) so long chats don’t bog down or crash the app. Downloads are available in common Linux formats (AppImage, Debian package, tarball), with additional packaging manifests for Flatpak, Snap, RPM, AUR, and Nix. -
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SmartGPT
A program that provides LLMs with ability to complete complex tasks
SmartGPT is an experimental autonomous agent framework built to help large language models tackle complex tasks with minimal or no additional user input. It works by decomposing larger objectives into smaller steps and gathering information from the internet and other outside sources as needed. The project is written in Rust and emphasizes modularity, allowing developers to compose different “Autos” depending on the workflow they want to build. Its architecture separates responsibility... -
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Whatlang-RS
Natural language detection library for Rust
Whatlang-RS is a Rust-based language detection library optimized for speed and accuracy, supporting a wide range of languages with probabilistic models. -
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hora
Efficient approximate nearest neighbor search algorithm collections
...These vectors are commonly generated by neural networks to represent images, text, audio, or other data types in a mathematical embedding space. The library is written in Rust and emphasizes performance, safety, and efficient memory management, making it suitable for production-grade applications requiring low latency and high throughput.
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