[Frontend] Add optional token-level progress bar to LLM.beam_search (#19301)

Signed-off-by: Ruosen Li <rxl190028@utdallas.edu>
Signed-off-by: Aaron Pham <contact@aarnphm.xyz>
Signed-off-by: Ubuntu <ubuntu@ip-172-31-71-179.ec2.internal>
Co-authored-by: 22quinn <33176974+22quinn@users.noreply.github.com>

Author: NekoMimiUnagi

vllm/entrypoints/llm.py

@@ -552,6 +552,7 @@ def beam_search(
         prompts: list[Union[TokensPrompt, TextPrompt]],
         params: BeamSearchParams,
         lora_request: Optional[Union[list[LoRARequest], LoRARequest]] = None,
+        use_tqdm: bool = False,
     ) -> list[BeamSearchOutput]:
         """
         Generate sequences using beam search.
@@ -561,6 +562,7 @@ def beam_search(
                 of token IDs.
             params: The beam search parameters.
             lora_request: LoRA request to use for generation, if any.
+            use_tqdm: Whether to use tqdm to display the progress bar.
         """
         # TODO: how does beam search work together with length penalty,
         # frequency, penalty, and stopping criteria, etc.?
@@ -623,7 +625,18 @@ def create_tokens_prompt_from_beam(
                     **mm_kwargs,
                 ), )
 
-        for _ in range(max_tokens):
+        token_iter = range(max_tokens)
+        if use_tqdm:
+            token_iter = tqdm(token_iter,
+                              desc="Beam search",
+                              unit="token",
+                              unit_scale=False)
+            logger.warning(
+                "The progress bar shows the upper bound on token steps and "
+                "may finish early due to stopping conditions. It does not "
+                "reflect instance-level progress.")
+
+        for _ in token_iter:
             all_beams: list[BeamSearchSequence] = list(
                 sum((instance.beams for instance in instances), []))
             pos = [0] + list(