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add pre-commit workflow and readme.md changes to point to debugging tools first

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dmahan93 2025-05-09 10:15:59 -05:00
parent d54376a617
commit baf2732f87
2 changed files with 18 additions and 3 deletions
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14
.github/workflows/pre-commit.yml vendored Normal file
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@ -0,0 +1,14 @@
name: pre-commit
on:
pull_request:
push:
branches: [main]
jobs:
pre-commit:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v3
- uses: pre-commit/action@v3.0.1

7
README.md
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@ -164,7 +164,7 @@ pre-commit install
2. **Run an Example Environment**
You should edit the config_init section of the environment file you want ([For example, in GSM8K Environment](https://github.com/NousResearch/atropos/blob/main/environments/gsm8k_server.py#L53)) to point to a running VLLM or SGLang inference server as well as any other configuration changes you'd like to make, such as the group size, then:
You should edit the config_init section of the environment file you want ([For example, in GSM8K Environment](https://github.com/NousResearch/atropos/blob/main/environments/gsm8k_server.py#L53)) to point to a running VLLM or SGLang inference server as well as any other [configuration changes](CONFIG.md) you'd like to make, such as the group size, then:
```bash
# Start the API server
@ -177,9 +177,10 @@ pre-commit install
# python environments/gsm8k_server.py serve --config environments/configs/example.yaml
# python environments/gsm8k_server.py serve --config environments/configs/example.yaml --env.group_size 8 # cli args override corresponding config settings
```
3. **Query the the API (Optional)**
3. **Grabbing Rollouts**
If you want to just query the api, start getting rollouts, and not use a trainer, see [API Docs](https://github.com/NousResearch/atropos/tree/main/atroposlib/api) to explore the REST API interface that this API exposes, if you plan to use a trainer, skip to step 4.
If you want to just start getting rollouts, and not use a trainer, see the [debug section](#testing-and-debugging-tools)
for help getting started with the available tools, we recommend starting with process or view-run
4. **Training Your Model**
- Follow our [training example guide](example_trainer/README.md) for detailed instructions