Merge pull request #294 from runpod-workers/feat/allow-config
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feat: allow config.yaml like vllm serve
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@@ -33,6 +33,17 @@ All behaviour is controlled through environment variables:
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**Pass any vLLM engine arg** not listed above by setting an env var with the **UPPERCASED** field name (e.g. `MAX_MODEL_LEN=4096`, `ENABLE_CHUNKED_PREFILL=true`). The worker auto-discovers all `AsyncEngineArgs` fields from env. See the [vLLM engine args docs](https://docs.vllm.ai/en/latest/configuration/engine_args) for all available options.
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**Configuration file:** You can also supply a `config.yaml` instead of (or alongside) env vars. Mount it at `/vllm_config.yaml` in the container, or set `VLLM_CONFIG_FILE` to a custom path. Use the same key names as `vllm serve` — hyphens and underscores both work:
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```yaml
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model: meta-llama/Llama-3.1-8B-Instruct
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max-model-len: 8192
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gpu-memory-utilization: 0.90
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quantization: awq
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```
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Environment variables always override config file values.
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For complete configuration options, see the [full configuration documentation](https://github.com/runpod-workers/worker-vllm/blob/main/docs/configuration.md).
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### Specify Transformers Version
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@@ -78,6 +78,20 @@ Configure worker-vllm using environment variables:
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Any env var whose name matches a valid `AsyncEngineArgs` field (uppercased) is applied automatically. Backward-compat aliases: `MODEL_NAME`, `TOKENIZER_NAME`, `MAX_CONTEXT_LEN_TO_CAPTURE`. This lets you configure any vLLM option without waiting for explicit worker support.
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### Configuration File (config.yaml)
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As an alternative to environment variables, you can supply a `config.yaml` file using the same key names as `vllm serve` (hyphens or underscores both work):
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```yaml
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model: meta-llama/Llama-3.1-8B-Instruct
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max-model-len: 8192
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gpu-memory-utilization: 0.90
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quantization: awq
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tensor-parallel-size: 2
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```
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Mount the file into the container at `/vllm_config.yaml`, or point to a custom path with the `VLLM_CONFIG_FILE` env var. Environment variables always take precedence over config file values.
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For the complete list of all available environment variables, examples, and detailed descriptions: **[Configuration](docs/configuration.md)**
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### Specify Transformers Version
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@@ -404,6 +404,23 @@ def _resolve_cached_model_path(model_name: str) -> str:
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return resolved
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def _get_args_from_config_file() -> dict:
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"""Load engine args from a vLLM-style config.yaml.
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Checks VLLM_CONFIG_FILE env var, then falls back to /vllm_config.yaml.
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Keys use the same long-form names as vllm serve (hyphens converted to underscores).
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"""
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import yaml
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path = os.getenv("VLLM_CONFIG_FILE", "/vllm_config.yaml")
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if not os.path.exists(path):
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return {}
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with open(path) as f:
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raw = yaml.safe_load(f) or {}
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normalized = {k.replace("-", "_"): v for k, v in raw.items()}
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logging.info("Loaded engine args from config file %s: %s", path, list(normalized.keys()))
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return normalized
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def get_local_args():
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"""
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Retrieve local arguments from a JSON file.
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@@ -429,6 +446,9 @@ def get_engine_args():
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# Start with worker custom defaults (only where we differ from vLLM)
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args = dict(DEFAULT_ARGS)
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# Config file values sit above defaults but below env vars
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args.update(_get_args_from_config_file())
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# Auto-discover: every AsyncEngineArgs field from env UPPERCASED (e.g. MAX_MODEL_LEN)
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args.update(_get_args_from_env_auto_discover())
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