Condense param filtering and move vllm import to local scope

libs/community/langchain_community/llms/vllm.py

@@ -5,7 +5,6 @@
 from langchain_core.outputs import Generation, LLMResult
 from langchain_core.utils import pre_init
 from pydantic import Field
-from vllm import SamplingParams
 
 from langchain_community.llms.openai import BaseOpenAI
 from langchain_community.utils.openai import is_openai_v1
@@ -124,21 +123,19 @@ def _generate(
         **kwargs: Any,
     ) -> LLMResult:
         """Run the LLM on the given prompt and input."""
+        from vllm import SamplingParams
 
         # build sampling parameters
         params = {**self._default_params, **kwargs, "stop": stop}
 
-        # Filter params for SamplingParams
-        sampling_param_keys = SamplingParams.__annotations__.keys()
-        sampling_params_dict = {
-            k: v for k, v in params.items() if k in sampling_param_keys
-        }
-
-        # Create SamplingParams instance for sampling
-        sampling_params = SamplingParams(**sampling_params_dict)
+        # filter params for SamplingParams
+        known_keys = SamplingParams.__annotations__.keys()
+        sample_params = SamplingParams(
+            **{k: v for k, v in params.items() if k in known_keys}
+        )
 
         # call the model
-        outputs = self.client.generate(prompts, sampling_params)
+        outputs = self.client.generate(prompts, sample_params)
 
         generations = []
         for output in outputs: