Enhance offline_inference_arctic.py with dynamic model path and better logging

inference/arctic/vllm/offline_inference_arctic.py

@@ -1,4 +1,10 @@
+import os
 from vllm import LLM, SamplingParams
+import logging
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 # Sample prompts.
 prompts = [
@@ -7,20 +13,25 @@
      "The capital of France is",
      "The future of AI is",
 ]
+
 # Create a sampling params object.
 sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
 
+# Fetch Arctic model path from environment variable or use default.
+arctic_model_path = os.getenv('ARCTIC_MODEL_PATH', '/checkpoint/arctic')
+logger.info(f'Using arctic model path: {arctic_model_path}')
+
 # Create an LLM.
-arctic_model_path = "/checkpoint/arctic"
 llm = LLM(model=arctic_model_path, 
           quantization="deepspeedfp",
           tensor_parallel_size=8)
+
 # Generate texts from the prompts. The output is a list of RequestOutput objects
 # that contain the prompt, generated text, and other information.
-
 outputs = llm.generate(prompts, sampling_params)
+
 # Print the outputs.
 for output in outputs:
     prompt = output.prompt
     generated_text = output.outputs[0].text
-    print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
+    logger.info(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")