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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
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