Wren is an open-source AI agent framework that simplifies building intelligent agents by orchestrating language model calls. It supports custom tool integration, memory management, and callback hooks, enabling developers to craft conversational assistants, automated research agents, and other intelligent workflows.
Wren is an open-source AI agent framework that simplifies building intelligent agents by orchestrating language model calls. It supports custom tool integration, memory management, and callback hooks, enabling developers to craft conversational assistants, automated research agents, and other intelligent workflows.
Wren is a Python-based AI agent framework designed to help developers create, manage, and deploy autonomous agents. It provides abstractions for defining tools (APIs or functions), memory stores for context retention, and orchestration logic to handle multi-step reasoning. With Wren, you can rapidly prototype chatbots, task automation scripts, and research assistants by composing LLM calls, registering custom tools, and persisting conversation history. Its modular design and callback capabilities make it easy to extend and integrate with existing applications.
Who will use Wren?
Developers
Machine Learning Engineers
AI Researchers
Data Scientists
Product Managers
How to use the Wren?
Step1: Install Wren via pip using `pip install getwren`.
Step2: Import Wren modules and initialize an Engine instance.
Step3: Register custom tools (functions or APIs) with the engine.
Step4: Configure a memory store for context retention across calls.
Step5: Invoke the agent with prompts or messages and handle responses.
Platform
web
mac
windows
linux
Wren's Core Features & Benefits
The Core Features
Tool registration and invocation
Memory management for context retention
Custom callback hooks
LLM orchestration and chaining
Easy Python SDK integration
The Benefits
Open-source and extensible
Modular architecture for rapid prototyping
Seamless tool and memory integration
Flexible callback and logging support
Simplifies complex agent workflows
Wren's Main Use Cases & Applications
Customer support chatbots with dynamic API lookups
Automated research assistants querying external data