Rigging is an open-source framework that lets developers build, test, and deploy AI agents with customizable tools, memory management, and multi-step workflow orchestration. It integrates with OpenAI and Hugging Face, providing type-safe interfaces, modular components, and extensible plugins to simplify complex agent behaviors and stateful conversations.
AI Platforms & Frameworks
Workflow Automation
#AI agent framework
#workflow orchestration
#TypeScript SDK
#memory management
#callback events
#Plugin-System
#model integration
#Chatbot Development
#data processing pipeline
#modular components
#reusable code
#logging system
#cross-model compatibility
#function registration
#development framework
#AI-Tools
#complex workflows
#debugging tools
#agent orchestration
#AI Development
...
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Rigging
Rigging is an open-source framework that lets developers build, test, and deploy AI agents with customizable tools, memory management, and multi-step workflow orchestration. It integrates with OpenAI and Hugging Face, providing type-safe interfaces, modular components, and extensible plugins to simplify complex agent behaviors and stateful conversations.
AI Platforms & Frameworks
Workflow Automation
#AI agent framework
#workflow orchestration
#TypeScript SDK
#memory management
#callback events
#Plugin-System
#model integration
#Chatbot Development
#data processing pipeline
#modular components
#reusable code
#logging system
#cross-model compatibility
#function registration
#development framework
#AI-Tools
#complex workflows
#debugging tools
#agent orchestration
#AI Development
...
Featured
What is Rigging?
Rigging is a developer-focused framework that streamlines the creation and orchestration of AI agents. It provides tool and function registration, context and memory management, workflow chaining, callback events, and logging. Developers can integrate multiple LLM providers, define custom plugins, and assemble multi-step pipelines. Rigging’s type-safe TypeScript SDK ensures modularity and reusability, accelerating AI agent development for chatbots, data processing, and content generation tasks.
Who will use Rigging?
- Software developers
- Machine learning engineers
- AI researchers
- Tech startups
- Research labs
How to use the Rigging?
- Step1: Install Rigging via npm install rigging
- Step2: Import Rigging and configure your preferred LLM provider
- Step3: Define and register tools, memory handlers, and utilities
- Step4: Create agent workflows by chaining nodes and callbacks
- Step5: Execute the agent, monitor output, and review logs
- Step6: Extend functionality with custom plugins and event hooks
Platform
- web
- mac
- windows
- linux
Rigging's Core Features & Benefits
The Core Features
- Tool and function registration
- Model integration (OpenAI, Hugging Face)
- Memory and context management
- Workflow and chain orchestration
- Callback events and logging
- Plugin and extension system
- TypeScript SDK with type safety
The Benefits
- Accelerates AI agent development
- Enables modular and reusable components
- Simplifies complex workflow orchestration
- Ensures cross-model compatibility
- Improves maintainability and debugging
Rigging's Main Use Cases & Applications
- Customer service chatbots with memory
- Automated data processing pipelines
- AI-driven content generation workflows
- Research assistant agents for analysis
- Monitoring and alerting agents
FAQs of Rigging
Rigging Company Information
Analytic of Rigging
Visit Over Time
Monthly Visits
1.1k
Avg Visit Duration
00:00:49
Page Per Visit
7.12
Bounce Rate
0.98%
Aug 2025 - Oct 2025 All Traffic
Geography
Top 2 Regions
United States
69.84%
Singapore
30.16%
Aug 2025 - Oct 2025 Worldwide Desktop Only
Traffic Sources
Direct
37.66%
Referrals
35.33%
Search
20.22%
Social
4.20%
Paid Referrals
1.12%
Mail
0.13%
Aug 2025 - Oct 2025 Desktop Only
Rigging Reviews
5/5
Rigging's Main Competitors and alternatives?
- LangChain
- LlamaIndex
- Haystack
- Botpress
- Rasa
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