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Description

OpenHarness is an open-source SDK developed in TypeScript, designed for developers aiming to create tailored AI-agent applications such as coding assistants, command-line tools, and web-based helpers. This toolkit features stateless agent execution, the ability to manage conversation states explicitly, and support for streaming events, alongside middleware that can be composed for retries, data persistence, and context management. Additionally, it supports hierarchical subagents and tools that operate under permission controls. Developers can easily link model providers via the Vercel AI SDK, enhance functionalities with the Model Context Protocol (MCP), and utilize filesystem or shell tools through customizable providers. The SDK includes React hooks and Vue composables to facilitate the integration of streaming agent outputs into various application interfaces. OpenHarness is available as an npm package and is designed for integration into projects that run on Node.js or edge environments, functioning as a developer-focused library rather than a service for end-users. Moreover, its architecture encourages flexibility and scalability in AI application development, allowing users to tailor their implementations to specific needs.

Description

TensorFlow Agents (TF-Agents) is an extensive library tailored for reinforcement learning within the TensorFlow framework. It streamlines the creation, execution, and evaluation of new RL algorithms by offering modular components that are both reliable and amenable to customization. Through TF-Agents, developers can quickly iterate on code while ensuring effective test integration and performance benchmarking. The library features a diverse range of agents, including DQN, PPO, REINFORCE, SAC, and TD3, each equipped with their own networks and policies. Additionally, it provides resources for crafting custom environments, policies, and networks, which aids in the development of intricate RL workflows. TF-Agents is designed to work seamlessly with Python and TensorFlow environments, presenting flexibility for various development and deployment scenarios. Furthermore, it is fully compatible with TensorFlow 2.x and offers extensive tutorials and guides to assist users in initiating agent training on established environments such as CartPole. Overall, TF-Agents serves as a robust framework for researchers and developers looking to explore the field of reinforcement learning.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

No images available

Screenshots View All

Integrations

Anthropic Yes 
Model Context Protocol (MCP) Yes 
OpenAI Yes 
Python No 
TensorFlow No 
Vercel AI SDK Yes 

Integrations

Anthropic No 
Model Context Protocol (MCP) No 
OpenAI No 
Python Yes 
TensorFlow Yes 
Vercel AI SDK No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

OpenHarness

Website

open-harness.dev/

Vendor Details

Company Name

Tensorflow

Founded

2015

Country

United States

Website

www.tensorflow.org/agents

Product Features

Product Features

Alternatives

No Alternatives

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