casibase

Next-generation personal AI assistant powered by LLM, RAG and agent loops Supporting computer-use, browser-use and coding agent

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✨ Overview

OpenAgent is an open-source personal AI assistant that brings together powerful LLMs, your own knowledge base, and autonomous agent loops — all in one self-hostable platform. Connect any model provider, build a RAG knowledge base from your documents, and let agents browse the web, run code, and call any MCP-compatible tool on your behalf.

📊 Usage Analytics	📋 Activity Monitoring
🛠️ Tool Management	🔍 Detailed Logs

📝 Note: Screenshots above showcase the built-in admin dashboard.

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🚀 Online Demo

🌐 Environment	URL	💡 Notes
Live Preview	https://demo.openagentai.org	Read-only tour — no account needed
Playground	https://try.openagentai.org	Make changes freely — data resets every 5 minutes

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📦 Quick Start

Pre-built binaries are available for Linux, macOS, and Windows (amd64 / arm64). The install script downloads the latest release, installs it, and starts the server on port 14000.

🔧 Install Binary (Recommended)

macOS / Linux / WSL

curl -fsSL --proto '=https' --tlsv1.2 \
  https://raw.githubusercontent.com/the-open-agent/openagent/master/scripts/install.sh | bash

Windows (PowerShell)

irm https://raw.githubusercontent.com/the-open-agent/openagent/master/scripts/install.ps1 | iex

Then open http://localhost:14000.

💡 Optional environment variables: OPENAGENT_VERSION, INSTALL_DIR, BIN_DIR.

🛠️ Build from Source

# Backend
go build

# Frontend
cd web && yarn install && yarn start

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🌟 Highlights

🔄 Agent Loops

Feature	Description
🌐 Browser-Use	Drive a real browser: navigate, click, fill forms, scrape, and screenshot pages
🔎 Web Search & Fetch	Search the web and pull page content directly into the agent's context
💻 Shell Execution	Run shell commands and scripts from within the agent loop
📄 Office Automation	Read and write Word, Excel, and PowerPoint files
🔌 MCP (Model Context Protocol)	Connect any MCP-compatible server over SSE, Stdio, or StreamableHTTP and expose its tools to the agent
👁️ Transparent Tool Calls	See exactly which tool was invoked, with what arguments, and what it returned, step by step

📚 RAG & Knowledge Base

Feature	Description
📤 Document Ingestion	Upload PDFs, Word docs, Excel sheets, and more; they are chunked, embedded, and indexed automatically
🔍 Semantic Search	Every chat retrieves the most relevant passages from your knowledge base before the LLM responds
🔗 Pluggable Embedding Providers	OpenAI, Azure, Gemini, Qwen, Cohere, Jina, HuggingFace, local models, and more
🗂️ Per-Store Isolation	Organise knowledge into separate stores and assign them to individual chats or applications

🤖 30+ Model Providers

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