DeepSWE

DeepSWE

Agentica Project
TF-Agents

TF-Agents

Tensorflow
+
+

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About

DeepSWE is a fully open source, state-of-the-art coding agent built on top of the Qwen3-32B foundation model and trained exclusively via reinforcement learning (RL), without supervised finetuning or distillation from proprietary models. It is developed using rLLM, Agentica’s open source RL framework for language agents. DeepSWE operates as an agent; it interacts with a simulated development environment (via the R2E-Gym environment) using a suite of tools (file editor, search, shell-execution, submit/finish), enabling it to navigate codebases, edit multiple files, compile/run tests, and iteratively produce patches or complete engineering tasks. DeepSWE exhibits emergent behaviors beyond simple code generation; when presented with bugs or feature requests, the agent reasons about edge cases, seeks existing tests in the repository, proposes patches, writes extra tests for regressions, and dynamically adjusts its “thinking” effort.

About

​TensorFlow Agents (TF-Agents) is a comprehensive library designed for reinforcement learning in TensorFlow. It simplifies the design, implementation, and testing of new RL algorithms by providing well-tested modular components that can be modified and extended. TF-Agents enables fast code iteration with good test integration and benchmarking. It includes a variety of agents such as DQN, PPO, REINFORCE, SAC, and TD3, each with their respective networks and policies. It also offers tools for building custom environments, policies, and networks, facilitating the creation of complex RL pipelines. TF-Agents supports both Python and TensorFlow environments, allowing for flexibility in development and deployment. It is compatible with TensorFlow 2.x and provides tutorials and guides to help users get started with training agents on standard environments like CartPole.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Software engineers, researchers, and developers seeking a solution to assist with real-world coding tasks such as bug-fixing, pull-request automation, and multi-file code edits

Audience

Academic researchers searching for a tool to develop and test new reinforcement learning algorithms within the TensorFlow ecosystem

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Agentica Project
Founded: 2025
United States
agentica-project.com

Company Information

Tensorflow
Founded: 2015
United States
www.tensorflow.org/agents

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LiteRT

LiteRT

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Categories

Categories

Integrations

Python
TensorFlow
Together AI

Integrations

Python
TensorFlow
Together AI
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