agentscope-ai/Trinity-RFT
Trinity-RFT is a general-purpose, flexible and scalable framework designed for reinforcement fine-tuning (RFT) of large language models (LLM).
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+18
STARS · LAST 30 DAYS
1
PER DAY
#630
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +18 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
Trinity-RFT gained 18 stars in the last 30 days, about 1 a day, and now has 703. It is about 1 year old and has averaged roughly 703 stars a year. It ranks #630 among Python repositories and #4,904 across all languages on GitHubRepo.
Trending Record
5
DAYS ON TRENDING
#3757
BEST RANK
Sep 29, 2026
FIRST APPEARANCE
Active
STATUS TODAY
Trinity-RFT has maintained a continuous presence across global trending indexes, peaking at #3757. Below is the 30-day activity profile:
💡 Overview
Trinity-RFT is an open-source project written in Python: Trinity-RFT is a general-purpose, flexible and scalable framework designed for reinforcement fine-tuning (RFT) of large language models (LLM).
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent, llm, rlhf. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install Trinity-RFT⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
Trinity-RFT coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with Trinity-RFT.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install Trinity-RFT using your package manager: `pip install Trinity-RFT`
Initialize your project workspace or configuration file for Trinity-RFT.
Import Trinity-RFT into your codebase or invoke it directly from your terminal.
Execute your test suite or run `Trinity-RFT --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
agentscope-ai/Trinity-RFT is currently ranked #4,904 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #4,897 | KiltMC/Kilt | Java | ★ 704 | Compare ↗ |
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| #4,897 | chao/RESTClient | JavaScript | ★ 704 | Compare ↗ |
| #4,904 | agentscope-ai/Trinity-RFT This Project | Python | ★ 703 | |
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Frequently Asked Questions
What does Trinity-RFT do? +
Trinity-RFT is a general-purpose, flexible and scalable framework designed for reinforcement fine-tuning (RFT) of large language models (LLM).
What language is Trinity-RFT written in? +
The primary language is Python. Topics include: agent, llm, rlhf.
Is Trinity-RFT actively maintained? +
Yes, the last recorded push was on Sep 29, 2026 with 56 open issues being tracked.
How many stars does Trinity-RFT have? +
Trinity-RFT has 703 stars and 83 forks on GitHub.
How does Trinity-RFT rank among GitHub repositories? +
With 703 stars, agentscope-ai/Trinity-RFT is ranked #4,904 globally across all repositories tracked on GitHubRepo and #630 among Python projects.
What license is Trinity-RFT distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
