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Misc CI fixes and Move Search-R1 to contrib (#410)
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.github/workflows/examples-chartqa.yml

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permissions:
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contents: read
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on:
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schedule:
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# Every day at 6 AM UTC+8
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- cron: "0 22 * * *"
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workflow_dispatch:
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repository_dispatch:
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types: [ci-chartqa, ci-all]
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run-name: >-
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${{ github.event_name == 'repository_dispatch'
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&& format(
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'ChartQA - PR #{0} - {1} - {2}',
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github.event.client_payload.pull_number,
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github.event.client_payload.ci_label,
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github.event.client_payload.correlation_id
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)
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|| format('ChartQA - {0}', github.event_name) }}
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jobs:
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chartqa:
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if: >

.github/workflows/tests.yml

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lint:
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strategy:
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matrix:
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setup: [fast, slow]
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setup: [fast, slow, next]
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fail-fast: false
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name: Lint - ${{ matrix.setup }}
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runs-on: ubuntu-latest
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- name: Sync dependencies (fast)
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run: uv sync --frozen --group dev --no-default-groups
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if: matrix.setup == 'fast'
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- name: Upgrade dependencies (next)
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run: uv lock --upgrade
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if: matrix.setup == 'next'
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- name: Sync dependencies (slow)
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run: |
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uv sync --frozen \
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--group agents \
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--group langchain \
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--no-default-groups
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if: matrix.setup == 'slow'
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if: matrix.setup != 'fast'
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# This pre-commit skips JavaScript on purpose.
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- name: Run pre-commit
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uses: pre-commit/action@v3.0.1
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if: matrix.setup == 'fast'
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- name: Run pyright (slow)
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run: uv run --locked --no-sync pyright -p pyrightconfig.json
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if: matrix.setup == 'slow'
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if: matrix.setup != 'fast'
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lint-js:
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name: Lint - JavaScript

agentlightning/verl/entrypoint.py

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@hydra.main(config_path="pkg://agentlightning/verl", config_name="config", version_base=None)
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def main(config: Any):
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from .daemon import AgentModeDaemon
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from .trainer import AgentLightningTrainer
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run_ppo(
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config,
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train_dataset=None,

contrib/CODEOWNERS

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# Put code owner definitions here.
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# Recipes
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recipes/search_r1 @SiyunZhao @JiahangXu
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## Overview
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5-
This example implements **Search R1** within Agent Lightning. It also serves as a demonstration of a **framework-free agent training pipeline**, showing how to run end-to-end RL training without relying on specialized frameworks. **It's tested and compatible with Agent-lightning v0.1.x**.
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This example implements **Search R1** within Agent Lightning. It also serves as a demonstration of a **framework-free agent training pipeline**, showing how to run end-to-end RL training without relying on specialized frameworks. **It's tested and compatible with Agent-lightning v0.1.2**.
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The example is designed to run on a single node with 8 GPUs, each having at least 40 GB of memory.
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