Search Results for "multi-system"
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Showing 61 open source projects for "multi-system"
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1
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. ... -
2
OpenFang
Open-source Agent Operating System
OpenFang is an open-source agent operating system designed to orchestrate autonomous AI agents and workflows in a structured, production-oriented environment. 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. ... -
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Ralph Orchestrator
An improved implementation of the Ralph Wiggum technique
Ralph Orchestrator is an AI workflow orchestration system designed to coordinate multiple agents, tools, and processes into structured pipelines that can execute complex tasks autonomously. It provides a framework for defining workflows where different components, such as LLMs, APIs, and custom functions, collaborate to achieve specific objectives. The system emphasizes modularity and composability, allowing developers to design workflows as reusable building blocks that can be combined or extended as needed. ... -
4
Moltis
A Rust-native claw you can trust
...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. -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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agentgateway
Next Generation Agentic Proxy for AI Agents and MCP servers
...The project supports interoperable protocols designed for this ecosystem, including Agent2Agent (A2A) and Model Context Protocol (MCP), which helps standardize how tools and agents interoperate. It is designed for performance and scale, implemented in Rust and engineered to handle large throughput and multi-tenant deployments. Operationally, it emphasizes safety and control with an RBAC system tuned for MCP/A2A use cases, plus the ability to update configuration dynamically via xDS without downtime. -
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Every Code
Local AI coding agent CLI with multi-agent orchestration tools
...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 various AI providers, enabling users to route tasks across different models depending on their needs. Every Code also includes browser integration and automation capabilities, extending its usefulness beyond simple code generation into more complex development tasks. ... -
7
mistral.rs
Fast, flexible LLM inference
...It provides multiple entry points for developers, including a CLI for running models locally and an HTTP server that exposes an OpenAI-compatible API surface for easy integration with existing clients. The project includes hardware-aware tooling that can benchmark a system and choose sensible quantization and device-mapping strategies, helping users get strong performance without manual tuning. It also supports serving multiple models from the same server process, enabling routing or quick switching between models depending on workload needs. For user-facing testing, mistral.rs can provide a built-in web UI, and it also offers a dedicated lightweight web chat interface that supports richer interaction patterns. -
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Meetily
Privacy first, AI meeting assistant with 4x faster Parakeet/Whisper
This project is a privacy-first AI meeting assistant that captures meeting audio, produces real-time transcripts, and generates summaries while keeping processing entirely on your own machine or infrastructure. It’s built for organizations that want meeting intelligence without sending recordings or transcripts to third-party cloud services, which helps address compliance and data sovereignty requirements. The app supports live transcription with local model options (including Whisper- and... -
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VT Code
VT Code - semantic AI coding agent
VTCode is a terminal-based AI coding agent designed to provide semantic code understanding and interactive assistance directly within a command-line environment. It is implemented in Rust and focuses on performance, portability, and deep integration with developer workflows that rely on terminal tools. The system leverages syntax-aware parsing technologies such as tree-sitter and AST-based analysis to understand code structure rather than relying solely on raw text, which enables more accurate and context-aware suggestions. VTCode operates as an agent rather than a simple autocomplete tool, meaning it can interpret user intent, navigate codebases, and assist with multi-step tasks. ... -
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10
Crabtalk
Agents daemon that hides nothing
...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. -
11
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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Kheish
Kheish: A multi-role LLM agent for tasks like code auditing
Kheish is a framework designed for cybersecurity professionals to automate penetration testing tasks, providing tools to streamline security assessments. -
13
Rewriting Project Claw Code
Ensure consistency and alignment between different codebases
Rewriting Project Claw Code is a development tool or framework designed to ensure consistency and alignment between different codebases, environments, or implementations. It focuses on maintaining parity across systems, which is particularly important in distributed architectures or multi-platform applications. The project provides mechanisms to compare, validate, and synchronize code or behavior, helping teams avoid discrepancies that can lead to bugs or inconsistencies. It may include automation tools that detect differences and enforce standards across repositories. The tool is useful in scenarios such as maintaining parity between frontend and backend logic, ensuring API consistency, or synchronizing multiple deployments. ... -
14
LangDB AI Gateway
Govern, secure, and optimize your AI traffic
...Developed by the LangDB team, AI Gateway acts as an intermediary between clients and backend LLMs, providing advanced features like caching, rate limiting, prompt management, and observability. It helps teams secure and optimize their LLM deployments, whether using local models or external APIs like OpenAI or Anthropic. With native support for multi-tenant environments and low-latency inference routing, AI Gateway is an essential tool for companies building production-grade generative AI services. -
15
Win-CodexBar
Show usage stats for OpenAI Codex and Claude Code
Win-CodexBar is a Windows system tray application that provides real-time visibility into usage limits and consumption across multiple AI coding tools. It is designed as a lightweight desktop utility that aggregates usage data from various providers and displays it in a compact, always-accessible interface. The app supports dozens of AI services, allowing developers to monitor API usage, quotas, and costs without logging into each platform individually. -
16
claurst
Your favorite Terminal Coding Agent, now in Rust
...The project likely explores how agents can be designed to handle complex workflows through modular components and clearly defined execution steps. It may include abstractions for managing context, decision-making, and interaction with external tools, enabling agents to perform multi-step tasks efficiently. The architecture suggests a focus on flexibility, allowing developers to adapt the system to different use cases or domains. It is likely intended as a lightweight but extensible platform for experimenting with agent behavior and orchestration. The project may also emphasize simplicity, making it accessible for developers who want to prototype agent systems quickly. -
17
HumanLayer
Open source IDE for orchestrating AI coding agents in large codebases
HumanLayer is an open source development environment designed to help developers orchestrate and manage AI coding agents working within complex software projects. It provides a framework and tooling that allow AI agents to research, plan, and implement changes in large codebases while maintaining structured workflows. It focuses on enabling AI-assisted development through coordinated agent workflows rather than isolated code generation tasks. HumanLayer integrates with modern AI models and... -
18
OpenAI Codex CLI
Lightweight coding agent that runs in your terminal
...Codex CLI can also handle multimodal inputs like screenshots and diagrams to implement features intelligently. The tool includes built-in sandboxing & security measures, such as network restrictions and directory confinement, to protect your system during code execution. With extensive configuration options, including multiple AI providers and custom guidance files, it fits seamlessly into developer environments. -
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CubeSandbox
Instant, Concurrent, Secure & Lightweight Sandbox for AI Agents
CubeSandbox is a lightweight, high-performance sandboxing environment designed to securely run AI agents and untrusted code in isolated containers. Built in Rust, it focuses on enabling concurrent execution while maintaining strong isolation and low overhead. The system is optimized for scenarios where multiple AI agents need to execute tasks in parallel without compromising system integrity. It provides fast startup times and efficient resource management, making it suitable for large-scale agent orchestration. CubeSandbox integrates well with cloud-native workflows and modern infrastructure pipelines. ... -
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Rig
Rust framework for building modular and scalable LLM-powered apps
...Its architecture emphasizes modularity, enabling developers to integrate only the components and integrations they need for a specific application. Rig includes built-in support for agent workflows, allowing systems to perform multi-turn reasoning, tool calling, and retrieval-based tasks within structured pipelines. It also supports capabilities such as text generation, embeddings, transcription, image generation, and audio generation depending on the provider used. Developers can integrate language models into their software with minimal boilerplate while maintaining flexibility for complex AI workflows. -
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LangChain Rust
LangChain for Rust, the easiest way to write LLM-based programs
...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. -
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Rivet
Visual AI IDE for building agents with prompt chains and graphs
Rivet is an open source visual AI programming environment designed to help developers build complex AI agents using a node-based interface and prompt chaining workflows. It provides a desktop application that allows users to visually construct and debug AI logic as interconnected graphs, making it easier to manage sophisticated interactions between language models and external tools. Rivet also includes a TypeScript library that enables these visual graphs to be executed and integrated... -
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Cake
Distributed LLM and StableDiffusion inference
Cake is a compact, powerful toolkit that combines a flexible TCP/UDP proxy, port forwarding system, and connection manager designed for both development and penetration testing scenarios. It enables users to create complex networking flows where traffic can be proxied, relayed, and manipulated between endpoints — useful for debugging networked applications, inspecting protocols, or tunneling traffic through different hops. The tool is designed to work with multiple protocols and supports dynamic rule definitions so that incoming and outgoing connections can be routed, rewritten, or logged according to user-defined policies. ... -
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OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
...OpenShell also features a privacy-aware routing system that prevents sensitive information from leaving the sandbox environment. By combining container isolation, policy enforcement, and agent orchestration, OpenShell offers a secure infrastructure for developing and operating AI agents. -
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herdr
Agent multiplexer that lives in your terminal
...Users can organize agent sessions into workspaces, tabs, and split panes while keeping visibility into what each agent is doing. The sidebar shows whether agents are blocked, working, done, or idle, so large multi-agent workflows are easier to supervise. Sessions continue running after detach, which allows users to reconnect later from another terminal or over SSH. The project is distributed as a lightweight Rust binary for Linux, macOS, and beta Windows support. It also includes a local socket API and CLI so agents can create panes, read output, and orchestrate terminal workflows themselves.
