[Frontend] Score entrypoint support data_1 & data_2 and queries & documents as inputs (#32577)

Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io>

examples/offline_inference/basic/score.py

@@ -21,8 +21,8 @@ def parse_args():
 
 def main(args: Namespace):
     # Sample prompts.
-    text_1 = "What is the capital of France?"
-    texts_2 = [
+    query = "What is the capital of France?"
+    documents = [
         "The capital of Brazil is Brasilia.",
         "The capital of France is Paris.",
     ]
@@ -32,13 +32,13 @@ def main(args: Namespace):
     llm = LLM(**vars(args))
 
     # Generate scores. The output is a list of ScoringRequestOutputs.
-    outputs = llm.score(text_1, texts_2)
+    outputs = llm.score(query, documents)
 
     # Print the outputs.
     print("\nGenerated Outputs:\n" + "-" * 60)
-    for text_2, output in zip(texts_2, outputs):
+    for document, output in zip(documents, outputs):
         score = output.outputs.score
-        print(f"Pair: {[text_1, text_2]!r} \nScore: {score}")
+        print(f"Pair: {[query, document]!r} \nScore: {score}")
         print("-" * 60)