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CI badge should point to main branch #422

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Merged
merged 2 commits into from
Oct 15, 2025
Merged

CI badge should point to main branch #422

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casteryh Oct 15, 2025
624ac3f
Remove hourly schedule for unit tests
casteryh Oct 15, 2025
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8 changes: 7 additions & 1 deletion .github/workflows/unit_test.yaml
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Expand Up @@ -2,7 +2,13 @@ name: Unit Tests

on:
pull_request:

schedule:
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Why would we run this every hour?

Should only run on PR and push to main

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done

# Runs every hour
- cron: '0 * * * *'
push:
branches: [ main ]
pull_request:
workflow_dispatch:

jobs:
unit_tests:
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4 changes: 2 additions & 2 deletions README.md
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@@ -1,8 +1,8 @@
# <img width="35" height="35" alt="image" src="https://github.com/user-attachments/assets/2700a971-e5d6-4036-b03f-2f89c9791609" /> Forge

#### A PyTorch-native agentic RL library that lets you focus on algorithms—not infra.
[![Unit Tests](https://github.com/meta-pytorch/forge/actions/workflows/unit_test.yaml/badge.svg)](https://github.com/meta-pytorch/forge/actions/workflows/unit_test.yaml)
[![GPU Tests](https://github.com/meta-pytorch/forge/actions/workflows/gpu_test.yaml/badge.svg)](https://github.com/meta-pytorch/forge/actions/workflows/gpu_test.yaml)
[![Unit Tests](https://github.com/meta-pytorch/forge/actions/workflows/unit_test.yaml/badge.svg?branch=main)](https://github.com/meta-pytorch/forge/actions/workflows/unit_test.yaml?query=branch%3Amain)
[![GPU Tests](https://github.com/meta-pytorch/forge/actions/workflows/gpu_test.yaml/badge.svg?branch=main)](https://github.com/meta-pytorch/forge/actions/workflows/gpu_test.yaml?query=branch%3Amain)

## Overview
The primary purpose of the Forge ecosystem is to delineate infra concerns from model concerns thereby making RL experimentation easier. Forge delivers this by providing clear RL abstractions and one scalable implementation of these abstractions. When you need fine-grained control over placement, fault handling/redirecting training loads during a run, or communication patterns, the primitives are there. When you don’t, you can focus purely on your RL algorithm.
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