Clouisle

Open-Source AI Agent Platform with Workflow Automation & Knowledge Management

Build, deploy, and manage intelligent AI agents with RAG-powered knowledge retrieval, visual workflow automation, and enterprise-grade security.

Official Website · 简体中文 · Features · Quick Start · Architecture · Documentation

---

Table of Contents

• Why Clouisle
• Features
• Quick Start
• Architecture
• Configuration
• Use Cases
• Roadmap
• Documentation
• Contributing
• Contributors
• License

---

---

Why Clouisle?

Modern enterprises face a common challenge: data fragmentation, low reusability, and zero intelligence execution. Knowledge is scattered across documents, databases, wikis, and internal tools — but when decisions need to be made, that knowledge remains static and non-actionable.

Clouisle transforms this reality by providing:

• Intelligent Knowledge Management: Hybrid search (vector + lexical) with reranking, configurable chunking, and multi-format document processing
• Agent-Native Architecture: AI agents that retrieve, reason, execute tools, and generate media — with streaming, thinking/reasoning mode, and conversation memory
• Visual Workflow Automation: Drag-and-drop workflow builder with 15+ node types, versioning, and multiple execution triggers
• Enterprise-Grade Security: Multi-tenancy, RBAC, SSO (OIDC/SAML/CAS), TOTP two-factor authentication, and comprehensive audit logging
• Flexible Integration: 24+ LLM providers, MCP tool protocol, sandboxed code execution, and API key management

Think of Clouisle as a living intelligence layer that evolves with your business.

---

Features

AI Agent Management

• Multi-Model Support: Configure agents with different LLM providers, parameters, and thinking/reasoning modes
• RAG Integration: Multiple retrieval modes — disabled, citation, and rewrite — with knowledge base binding
• Streaming & Thinking: Real-time streaming responses with reasoning/thinking content support
• Conversation Management: Multi-turn conversations with branching, manual stop, token usage tracking, and session memory
• Media Generation: Built-in support for text-to-image, video, and audio generation within conversations
• Tool System: Built-in tools (web search, calculator, file parser), custom HTTP API tools, and MCP protocol integration
• Context Compression: Automatic conversation context compression for long-running sessions
• Visibility Control: Private, team, or public access levels with RBAC enforcement

Visual Workflow Builder

• No-Code Interface: Drag-and-drop workflow creation with real-time node configuration
• 15+ Node Types: LLM, Agent, Condition, Code Execution (Python), Knowledge Retriever, HTTP Request, Tool, Sub-workflow, Media Generation, Iteration, and more
• Execution Triggers: Manual, scheduled (Cron), webhook, or API — flexible for any use case
• Versioning: Draft/publish lifecycle with version history and rollback
• Real-Time Monitoring: Streaming execution with live node-level status updates
• Debug Mode: Step-by-step testing with variable inspection before deployment
• Sub-Workflows: Nest and reuse workflows as sub-workflow nodes
• Profiling & Metrics: Execution profiling with per-node latency and cost tracking

Knowledge Base System

• Multi-Format Support: PDF, DOCX, XLSX, Markdown, and more via MarkItDown
• Hybrid Search: Vector similarity (Qdrant) + BM25 lexical search (pg_search) with Reciprocal Rank Fusion
• Configurable Chunking: Customizable chunk size, overlap, and separator with preview
• Reranking: Optional reranking pipeline to improve retrieval accuracy
• Embedding Management: Configurable embedding models and vector dimensions
• Async Document Processing: Background processing via Celery with status tracking
• Lexical Search: PostgreSQL-powered full-text search with Chinese segmentation (jieba)
• Search Modes: Vector-only, full-text only, or hybrid with configurable weight tuning

LLM Provider Support

Supports 24+ providers out of the box, plus any OpenAI-compatible endpoint.

Chat & Completion

Provider	Representative Models
OpenAI	GPT-5.6 Sol, GPT-5.6 Terra, GPT-5.6 Luna
Anthropic	Claude Opus 5, Fable 5, Mythos 5, Sonnet 5
Google	Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, Gemini 3.1 Pro
xAI	Grok 4.5, Grok 4.6 (upcoming), Grok 4.7 (upcoming)
Azure OpenAI	GPT-5.6 Sol, GPT-5.6 Luna, GPT-5.4 series
DeepSeek	DeepSeek-V4, DeepSeek-V4-Flash
Moonshot	Kimi K3 (2.8T params, open-source)
Zhipu	GLM-5.2, GLM-4.7
Qwen	Qwen3.8-Max, Qwen3.7-Flash
Baichuan	Baichuan-M4
MiniMax	MiniMax-M3 (1M context, multimodal)
Volcengine	Doubao 2.1 Pro / Turbo
SiliconFlow	GLM-5.2, MiniMax-M3, Nex-N2-Pro, and other open models
Ollama	Local models via Ollama
Custom	Any OpenAI-compatible endpoint

Image, Video & Audio

Provider	Latest Models	Modality
OpenAI	GPT image-2, GPT image-1.5	Text-to-Image
Stability AI	Stable Diffusion 3.5 Large, Stable Audio 3.0	Image, Audio
Midjourney	V8.2, V8.1	Text-to-Image (via proxy)
Google	Imagen 4, Imagen 3	Text-to-Image
Runway	Gen-4.5, Aleph 2.0	Text-to-Video
Pika	Pika 2.5, PikaStream 1.0	Text-to-Video
Luma	Ray3.2, Uni-1.1	Image, Video
Kling	Kling 3.0, Kling IMAGE 3.0 Omni	Image, Video (native 4K)
MiniMax	H3, M3	Image, Video, TTS, Audio
Volcengine	Seedance 2.5, Doubao 2.1 Pro	Image, Video, TTS, Audio
SiliconFlow	FLUX 1.1 Pro, Wan2.2, CosyVoice2, Fish-Speech	Image, Video, Audio

Model Management

• Multi-Provider: Centralized model configuration across 24+ providers with standardized interfaces
• Model Registry: Register and manage chat, embedding, rerank, TTS, STT, image, and video models
• Team Authorization: Granular per-team model access control with daily/monthly token and request quotas
• Connection Testing: Built-in model connectivity testing before deployment
• Default Parameters: Configurable per-model defaults (temperature, top_p, max_tokens, thinking, etc.)
• Capability Markers: Tag models with capabilities (vision, function calling, streaming, etc.)
• Encrypted Credentials: Secure API key storage with encryption at rest

Enterprise Features

• Multi-Tenancy: Team-based resource isolation with granular model authorization and quota tracking
• RBAC: Role-based permission system with custom roles and permission presets
• SSO: OIDC, OAuth2, SAML 2.0, and CAS single sign-on support
• Two-Factor Authentication: TOTP-based 2FA for enhanced account security
• Audit Logging: Comprehensive action tracking with before/after snapshots and user attribution
• Notification System: In-app, email, DingTalk, WeChat Work, Feishu, Slack, and webhook channels
• API Key Management: Scoped API keys with expiration, usage tracking, and team access control
• Site Settings: Configurable site-wide settings with localization support (en/zh)
• Password Policies: Configurable expiration, history, and complexity requirements

Tool System

• Built-in Tools: Time/Date, Calculator, Web Search (Tavily), File Parser, and Python Code Interpreter
• Custom Tools: Configurable HTTP API tools with authentication (API key, Bearer, Basic) and variable mapping
• MCP Integration: Model Context Protocol for standardized tool capabilities and resource access
• Sandboxed Execution: Secure, isolated Python code execution environment with resource limits
• Tool Registry: Centralized tool management with credential injection and lifecycle hooks

---

Quick Start

Prerequisites

• Docker & Docker Compose

For development from source, see the Development Guide.

1. Configure Environment

# Copy the Docker deployment environment file
cp deploy/.env.example deploy/.env

# Edit deploy/.env with secure random values for:
#   SECRET_KEY, POSTGRES_PASSWORD, REDIS_PASSWORD, QDRANT_API_KEY

2. Start Clouisle

cd deploy
docker compose --env-file .env up -d

3. Access the Application

• Frontend: http://localhost:3000
• API Documentation: http://localhost:8000/docs

For local development setup (backend + frontend from source), see the Development Guide.

---

Architecture

┌─────────────────────────────────────────────────────────────────┐
│                         Frontend (Next.js 16)                    │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────────────┐ │
│  │ Dashboard│  │ Platform │  │   Chat   │  │  Auth (SSO/Login)│ │
│  └──────────┘  └──────────┘  └──────────┘  └──────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
                                  │
                                  ▼
┌─────────────────────────────────────────────────────────────────┐
│                      Backend (FastAPI)                           │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────────────┐ │
│  │  Agents  │  │ Workflows│  │Knowledge │  │  Users & Teams   │ │
│  │  Engine  │  │  Engine  │  │  Bases   │  │    Management    │ │
│  └──────────┘  └──────────┘  └──────────┘  └──────────────────┘ │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────────────┐ │
│  │   LLM    │  │   Tool   │  │  Audit   │  │   Notification   │ │
│  │ Adapters │  │  System  │  │ Logging  │  │     Service      │ │
│  └──────────┘  └──────────┘  └──────────┘  └──────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
                                  │
                    ┌─────────────┼─────────────┐
                    ▼             ▼             ▼
             ┌──────────┐  ┌──────────┐  ┌──────────┐
             │PostgreSQL│  │  Redis   │  │  Qdrant  │
             │   (DB)   │  │ (Cache)  │  │ (Vector) │
             └──────────┘  └──────────┘  └──────────┘

Tech Stack

Backend

• Framework: FastAPI (Python 3.13)
• ORM: Tortoise ORM with AsyncPG
• Task Queue: Celery + Redis
• Vector DB: Qdrant
• LLM Framework: LangChain + LangGraph

Frontend

• Framework: Next.js 16 (App Router)
• Runtime: Bun
• UI: shadcn/ui + Tailwind CSS
• Language: TypeScript

---

Configuration

Environment Variables

Key configuration options (see .env.example for full list):

Variable	Description
DATABASE_URL	PostgreSQL connection string (auto-built from individual vars if unset)
POSTGRES_SERVER / POSTGRES_PORT / POSTGRES_USER / POSTGRES_PASSWORD / POSTGRES_DB	PostgreSQL connection details
REDIS_HOST / REDIS_PORT / REDIS_PASSWORD	Redis connection
QDRANT_URL / QDRANT_API_KEY	Qdrant vector database
SECRET_KEY	JWT signing key
VECTOR_BACKEND	Vector DB backend (default: qdrant)
API_BASE_URL	Public API URL for the backend
FRONTEND_URL	Frontend URL for CORS and redirects
NEXT_PUBLIC_API_URL	API URL consumed by the frontend
TAVILY_API_KEY	Web search API key (optional)
SANDBOX_RUNTIME_ENABLED	Enable sandboxed code execution

Site Settings

Configure via the admin dashboard:

• General: Site name, description, branding
• Security: Password policies, session timeout, login limits
• Registration: Enable/disable, require approval, email verification
• Email: SMTP configuration for notifications
• SSO: Configure identity providers
• Notifications: Auto-notification rules and channels

---

Documentation

• User and operator docs: docs/guide/README.md
• Developer and architecture docs: docs/dev/README.md

---

Use Cases

Use Case	Description
Enterprise Q&A	Deploy AI agents grounded in your internal knowledge with hybrid search and reranking for accurate, context-aware answers across documents
Workflow Automation	Build no-code workflows combining LLM reasoning, API integrations, code execution, and branching logic
Customer Support	Create intelligent support agents with knowledge base access, conversation memory, and escalation workflows
Content Generation	Automate text, image, video, and audio generation pipelines with AI agents and media generation nodes
Data Analysis	Connect agents to internal databases and APIs for natural-language data querying and reporting
Compliance & Risk	Automate document analysis for contracts, policies, and regulatory requirements with audit trails
Engineering Productivity	Accelerate onboarding with instant access to documentation and tribal knowledge via RAG agents

---

Roadmap

• Multi-provider LLM support (15+ providers)
• Visual workflow builder
• Knowledge base with RAG
• Enterprise SSO (OIDC, SAML, OAuth2)
• Multi-channel notifications
• Comprehensive audit logging
• Industry-specific agent templates
• Advanced analytics dashboard
• Plugin marketplace
• Mobile application

---

Contributing

We welcome contributions! Please see our Contributing Guide for details.

For development setup and commands (lint, test, build), see the Development Guide.

Contributors

Thanks to all the people who have contributed to Clouisle:

License

Clouisle is open-sourced under the GPL v3 license.

---

Acknowledgments

Clouisle is built on the shoulders of many outstanding open-source projects — from FastAPI and LangChain on the backend to Next.js and shadcn/ui on the frontend, plus infrastructure pillars like PostgreSQL, Redis, and Qdrant.

See ACKNOWLEDGMENTS.md for the full list.

---

Star History

---

Star us on GitHub to support the project
PRs are welcome · Build the future of enterprise AI together