Search Results for "multi language"
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Showing 25 open source projects for "multi language"
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Cherry Studio
Cherry Studio is a desktop client that supports for multiple LLMs
Cherry Studio is a cross-platform desktop client that integrates multiple large language model providers into a unified interface for creating and using AI assistants, supporting customization and multi-model conversations. Selection Assistant with smart content selection enhancement. Deep Research with advanced research capabilities. Memory System with global context awareness. Document Preprocessing with improved document handling. -
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oh-my-claudecode
Teams-first Multi-agent orchestration for Claude Code
oh-my-claudecode is a multi-agent orchestration framework designed to dramatically simplify and enhance the use of Claude Code by providing a zero-configuration, high-level interface for managing complex AI-driven development workflows. The project abstracts away the complexity of interacting with multiple AI agents by introducing a “team-based” execution model, where tasks are automatically decomposed into planning, execution, verification, and iteration stages. -
3
DeepChat
A smart assistant that connects powerful AI to your personal world
DeepChat is an open‑source, multi‑model AI chat platform featuring a unified interface for cloud and local language models, enriched with tool‑calling capabilities, search enhancements, privacy protection, and extensive model support. DeepChat is a powerful open-source AI chat platform providing a unified interface for interacting with various large language models. -
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Accomplish
Accomplish is the open source Al coworker that lives on your desktop
Accomplish is an open-source AI desktop agent that automates everyday computer tasks directly on a user’s machine. It can handle file management, document creation, and browser-based workflows through natural language instructions. The system runs locally, ensuring that user data remains private and under full control. It supports integration with multiple AI providers or local models, giving users flexibility in how intelligence is powered. Accomplish emphasizes autonomy, allowing it to execute multi-step tasks without constant supervision. ... -
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5
OpenClaw CN
The Chinese version of OpenClaw
OpenClaw-CN is a Chinese language community adaptation and localization of the OpenClaw project, focused on making a powerful open-source agent framework usable and understandable for Chinese-speaking developers. It includes translated documentation, localized examples, and language-specific nuances so that developers in the Chinese ecosystem can adopt and contribute without a language barrier. -
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Kimchi
Terminal coding agent powered by Kimchi's multi-model orchestration
Kimchi is a terminal coding agent powered by multi-model orchestration. It is designed to help developers run AI-assisted coding sessions from the command line while coordinating specialized agents, tools, permissions, and project context. The repository includes systems for subagents, task classification, model delegation, MCP integration, web search, web fetching, Language Server Protocol support, authentication, and interactive terminal workflows. -
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OpenClaw
Your own personal AI assistant. Any OS. Any Platform.
OpenClaw (formerly Clawdbot/Moltbot) is an open-source, self-hosted autonomous AI assistant designed to run on user-controlled hardware and bridge conversational natural language with real-world task execution, effectively acting as a proactive digital assistant rather than a reactive chatbot. It lets you send instructions through familiar messaging platforms like WhatsApp, Telegram, Discord, Slack, Signal, iMessage, and more, and then interprets those instructions to carry out actions such... -
8
Ax
Build LLM powered Agents and "Agentic workflows"
...Seamlessly integrates with multiple LLMs and VectorDBs to build RAG pipelines or collaborative agents that can solve complex problems. Advanced features streaming validation, multi-modal DSPy, etc. We've renamed from "llmclient" to "ax" to highlight our focus on powering agentic workflows. We agree with many experts like "Andrew Ng" that agentic workflows are the key to unlocking the true power of large language models and what can be achieved with in-context learning. Also, we are big fans of the Stanford DSPy paper, and this library is the result of all of this coming together to build a powerful framework for you to build with. -
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Dexter
An autonomous agent for deep financial research
Dexter is an autonomous agent tailored for deep financial research: you pose complex financial questions (for example, about a company’s revenue growth or financial ratios) and Dexter breaks them down into structured research tasks, fetches relevant real-time data (e.g. income statements, cash flows), performs analysis, and returns data-backed answers. It uses a multi-agent architecture with components such as a planning agent (to decompose queries), an action agent (to run tasks & fetch... -
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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10
Agentic Coding Flywheel Setup
System tool for beginners wanting agentic engineering capabilities
Agentic Coding Flywheel Setup (ACFS) is a comprehensive environment bootstrap project that configures a full stack of tools for autonomous AI-assisted coding workflows. With a single shell installer, ACFS transforms a fresh compute environment into a ready-to-use development setup that includes modern shells, language runtimes, AI coding agents (like Claude Code, Codex CLI, and Gemini CLI), and a coordinated toolchain for orchestration and safety. The system is designed for developers who want to run multi-agent coding assistants on personal or VPS hosts with minimal manual configuration. It comes with a battle-tested suite of utilities for agent coordination, orchestration, and developer productivity enhancements, such as named tmux panes, agent mail coordination layers, and cloud CLI integrations. -
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Model Context Protocol (MCP)
Specification and documentation for the Model Context Protocol
Model Context Protocol is an open protocol that standardizes how LLM applications connect to external data sources, tools, and runtime context. It separates the concern of providing context from the model interaction itself, allowing AI applications to access resources through a common interface. The project includes the specification, documentation, SDKs, maintained servers, and community infrastructure around the protocol. MCP is useful for AI-powered IDEs, chat systems, agent platforms,... -
12
Eko
Build Production-ready Agentic Workflow with Natural Language
Eko (Eko Keeps Operating) is a JavaScript framework designed for building production-ready agent-based workflows using natural language commands. It allows developers to create automated agents that can handle complex workflows in both computer and browser environments. With a focus on high development efficiency, Eko simplifies the creation of multi-step workflows, enabling users to integrate and automate tasks across platforms. It provides a unified interface for managing agents, offering features such as web resource access and high task complexity handling. ... -
13
EASY LLM CLI
An open-source AI agent that is compatible with multiple LLM models
...The CLI can help with coding tasks, command workflows, file understanding, and project navigation. Its main value is bringing multi-provider AI assistance into a practical terminal environment. -
14
Dive
Dive is an open-source MCP Host Desktop Application
Dive is an open‑source MCP host desktop application that serves as a bridge between MCP servers and any large language models supporting function calling, designed to deliver a seamless AI agent experience across environments. Compatible with ChatGPT, Anthropic, Ollama and OpenAI-compatible models. Enabling seamless MCP AI agent integration on both stdio and SSE mode. One-click access to managed MCP servers via OAPHub.ai - eliminates complex local deployments. Modern Tauri version alongside... -
15
LibreChat
Enhanced ChatGPT Clone: Features Agents, MCP, DeepSeek, Anthropic, etc
LibreChat is an open-source AI chat platform designed to give users full control over their conversational AI experience by letting them self-host and integrate with a wide range of large language models. It serves as a flexible alternative to commercial AI chat services by allowing connections to providers like OpenAI, Anthropic Claude, Google Vertex, AWS Bedrock, and more, all while keeping your data private on infrastructure you control. The project features a sleek, intuitive interface... -
16
WorkAny
Desktop Agent for Any Task
WorkAny is an open-source desktop AI agent application that executes generic tasks through natural language commands, effectively bringing intelligent automation into everyday workflows without needing to write code manually. It acts as a unified environment where users can ask the AI to generate documents, presentations, websites, spreadsheets, organize files, or write code — all with real-time streaming outputs directly in the app, so you see results as the AI produces them. Powered by a... -
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OpenClaw Opik Observability Plugin
Official plugin for OpenClaw that exports agent traces to Opik
...The project integrates directly with OpenClaw’s plugin architecture so that developers can capture detailed runtime information about how their agents behave while executing tasks. Each time an AI agent performs an action—such as calling a large language model, invoking a tool, accessing memory, or delegating to a sub-agent—the plugin records the full interaction and sends it to Opik for analysis and visualization. This allows developers to inspect inputs, outputs, token usage, latency, and execution flow across complex multi-step agent workflows. The goal of the project is to provide transparency into the internal reasoning and operational pipeline of agent systems so developers can diagnose failures, control costs, and improve reliability. -
18
DenchClaw
Fully Managed OpenClaw Framework for all knowledge work ever
DenchClaw is a local-first AI-powered CRM and productivity platform built on top of the OpenClaw framework, designed to transform a user’s entire computer into a programmable, agent-driven workspace. Unlike traditional cloud-based CRMs or AI tools, it runs entirely on the user’s machine and exposes a web interface locally, allowing full control over data, workflows, and automation without relying on external servers. The system combines database management, browser automation, and AI... -
19
OpenClaw-RL
Train any agents simply by 'talking'
OpenClaw-RL is an open-source reinforcement learning framework designed to train and personalize AI agents built on the OpenClaw ecosystem. The project focuses on enabling agents to improve their behavior through interactive learning rather than relying solely on static prompts or predefined skills. One of its key ideas is allowing users to train an AI agent simply by interacting with it conversationally, using natural language feedback to guide the learning process. The system incorporates... -
20
AgentDock
Build Anything with AI Agents
AgentDock is an open-source framework designed to simplify the development, orchestration, and deployment of AI agents capable of executing complex automated workflows. The platform provides a backend-first architecture that allows developers to create sophisticated agent systems while maintaining flexibility in model providers and infrastructure choices. It consists of two main components: a core framework that handles agent logic and orchestration, and a reference client application that... -
21
VoltAgent
Open Source TypeScript AI Agent Framework
...It simplifies the development of AI agent applications by providing modular building blocks, standardized patterns, and abstractions. Whether you're creating chatbots, virtual assistants, automated workflows, or complex multi-agent systems, VoltAgent handles the underlying complexity, allowing you to focus on defining your agents' capabilities and logic. -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher... -
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Gradient Bang
Gradient Bang is an online multiplayer universe
Gradient Bang is an experimental open-source project developed within the Pipecat ecosystem that reimagines AI interaction as a persistent, multiplayer simulation where users and large language models coexist inside a shared virtual environment. Rather than functioning as a traditional application or API, it is conceptualized as an “online multiplayer universe” in which participants can explore, trade, battle, and collaborate while interacting with AI agents as active entities within the... -
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Botpress
Dev tools to reliably understand text and automate conversations
...We propose you a complete dev-friendly platform that ships with all the tools you need to build, deploy and manage production-grade chatbots in record time. Built-in Natural Language Processing tasks such as intent recognition, spell checking, entity extraction, and slot tagging (and many others). A visual conversation studio to design multi-turn conversations and workflows. An emulator & a debugger to simulate conversations and debug your chatbot. Support for popular messaging channels like Slack, Telegram, MS Teams, Facebook Messenger, and an embeddable web chat. ... -
25
SynquoRum
Multi-AI workspace with persistent cross-session memory via MCP
SynquoRum is a multi-AI workspace for people who use multiple language models daily and are tired of fragmented context when switching tools. Most AI products treat memory as belonging to the model. Every new session starts from zero. SynquoRum inverts this: memory belongs to the workspace, not to any specific agent. Through an MCP (Model Context Protocol) server with 22 tools, the workspace exposes its memory to any MCP-compatible client — Claude.ai, Cursor, Cline, custom agents — so the same context follows you across providers and sessions. ...
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