Agent-Q

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agent-q is an open-source tool for developing autonomous AI agents with advanced reasoning and learning capabilities. It utilizes various agentic architectures to reliably complete tasks on the web.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is agent-q?

agent-q is an open-source project designed for building advanced autonomous AI agents capable of reasoning and learning. It leverages multiple agentic architectures, including planner-navigator, solo planner-actor, and actor-critic models, to reliably execute tasks on the web. The tool also incorporates Monte Carlo Tree Search-based reinforcement learning and DPO finetuning for enhanced performance. This repository provides an open-source implementation of the research paper "Agent Q," offering developers a robust framework for creating sophisticated AI agents. It requires setting up a Chrome instance in dev mode and configuring OpenAI and Langfuse keys for full functionality.

Best used for

Ideal for developers and data scientists who need to build and deploy advanced autonomous AI agents, automate complex web interactions, and experiment with cutting-edge agentic architectures. Especially valuable for researchers and engineers looking to implement and extend the Agent Q research paper.

Common actions

build AI agents

automate web tasks

implement agent architectures

research AI learning

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Capabilities

Key features

Planner-navigator architecture
Solo planner-actor agent
Actor-critic architecture
Monte Carlo Tree Search
DPO finetuning
Web task completion

Target Audience

developerdata scientist

Integrations

openailangfuse

Pricing & Plans

Open Source

Free

FAQs

What are the primary agentic architectures implemented in agent-q?

agent-q includes a planner-navigator multi-agent architecture, a solo planner-actor agent, and an actor-critic multi-agent architecture. It also features an actor-critic architecture combined with Monte Carlo Tree Search and DPO finetuning for advanced learning capabilities.

What are the setup requirements for running agent-q?

To set up agent-q, you need to install Poetry for dependency management. Additionally, you must start a Chrome instance in dev mode with remote debugging enabled and configure your OpenAI and Langfuse API keys in the .env file.

Is Langfuse tracing mandatory for agent-q?

Langfuse is currently required by default for tracing. However, if you do not want tracing, you can modify the `base.py` file to directly import the OpenAI client and comment out the `@observe` decorator and related Langfuse code.

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