[Misc] Use NamedTuple in Multi-image example (vllm-project#8705)

Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com>

examples/offline_inference_vision_language_multi_image.py

@@ -4,8 +4,9 @@
 by the model.
 """
 from argparse import Namespace
-from typing import List
+from typing import List, NamedTuple, Optional
 
+from PIL.Image import Image
 from transformers import AutoProcessor, AutoTokenizer
 
 from vllm import LLM, SamplingParams
@@ -19,7 +20,15 @@
 ]
 
 
-def load_qwenvl_chat(question: str, image_urls: List[str]):
+class ModelRequestData(NamedTuple):
+    llm: LLM
+    prompt: str
+    stop_token_ids: Optional[List[str]]
+    image_data: List[Image]
+    chat_template: Optional[str]
+
+
+def load_qwenvl_chat(question: str, image_urls: List[str]) -> ModelRequestData:
     model_name = "Qwen/Qwen-VL-Chat"
     llm = LLM(
         model=model_name,
@@ -48,10 +57,16 @@ def load_qwenvl_chat(question: str, image_urls: List[str]):
 
     stop_tokens = ["<|endoftext|>", "<|im_start|>", "<|im_end|>"]
     stop_token_ids = [tokenizer.convert_tokens_to_ids(i) for i in stop_tokens]
-    return llm, prompt, stop_token_ids, None, chat_template
+    return ModelRequestData(
+        llm=llm,
+        prompt=prompt,
+        stop_token_ids=stop_token_ids,
+        image_data=[fetch_image(url) for url in image_urls],
+        chat_template=chat_template,
+    )
 
 
-def load_phi3v(question: str, image_urls: List[str]):
+def load_phi3v(question: str, image_urls: List[str]) -> ModelRequestData:
     llm = LLM(
         model="microsoft/Phi-3.5-vision-instruct",
         trust_remote_code=True,
@@ -62,10 +77,17 @@ def load_phi3v(question: str, image_urls: List[str]):
                              for i, _ in enumerate(image_urls, start=1))
     prompt = f"<|user|>\n{placeholders}\n{question}<|end|>\n<|assistant|>\n"
     stop_token_ids = None
-    return llm, prompt, stop_token_ids, None, None
+
+    return ModelRequestData(
+        llm=llm,
+        prompt=prompt,
+        stop_token_ids=stop_token_ids,
+        image_data=[fetch_image(url) for url in image_urls],
+        chat_template=None,
+    )
 
 
-def load_internvl(question: str, image_urls: List[str]):
+def load_internvl(question: str, image_urls: List[str]) -> ModelRequestData:
     model_name = "OpenGVLab/InternVL2-2B"
 
     llm = LLM(
@@ -93,10 +115,16 @@ def load_internvl(question: str, image_urls: List[str]):
     stop_tokens = ["<|endoftext|>", "<|im_start|>", "<|im_end|>", "<|end|>"]
     stop_token_ids = [tokenizer.convert_tokens_to_ids(i) for i in stop_tokens]
 
-    return llm, prompt, stop_token_ids, None, None
+    return ModelRequestData(
+        llm=llm,
+        prompt=prompt,
+        stop_token_ids=stop_token_ids,
+        image_data=[fetch_image(url) for url in image_urls],
+        chat_template=None,
+    )
 
 
-def load_qwen2_vl(question, image_urls: List[str]):
+def load_qwen2_vl(question, image_urls: List[str]) -> ModelRequestData:
     try:
         from qwen_vl_utils import process_vision_info
     except ModuleNotFoundError:
@@ -143,7 +171,13 @@ def load_qwen2_vl(question, image_urls: List[str]):
     else:
         image_data, _ = process_vision_info(messages)
 
-    return llm, prompt, stop_token_ids, image_data, None
+    return ModelRequestData(
+        llm=llm,
+        prompt=prompt,
+        stop_token_ids=stop_token_ids,
+        image_data=image_data,
+        chat_template=None,
+    )
 
 
 model_example_map = {
@@ -155,20 +189,17 @@ def load_qwen2_vl(question, image_urls: List[str]):
 
 
 def run_generate(model, question: str, image_urls: List[str]):
-    llm, prompt, stop_token_ids, image_data, _ = model_example_map[model](
-        question, image_urls)
-    if image_data is None:
-        image_data = [fetch_image(url) for url in image_urls]
+    req_data = model_example_map[model](question, image_urls)
 
     sampling_params = SamplingParams(temperature=0.0,
                                      max_tokens=128,
-                                     stop_token_ids=stop_token_ids)
+                                     stop_token_ids=req_data.stop_token_ids)
 
-    outputs = llm.generate(
+    outputs = req_data.llm.generate(
         {
-            "prompt": prompt,
+            "prompt": req_data.prompt,
             "multi_modal_data": {
-                "image": image_data
+                "image": req_data.image_data
             },
         },
         sampling_params=sampling_params)
@@ -179,13 +210,12 @@ def run_generate(model, question: str, image_urls: List[str]):
 
 
 def run_chat(model: str, question: str, image_urls: List[str]):
-    llm, _, stop_token_ids, _, chat_template = model_example_map[model](
-        question, image_urls)
+    req_data = model_example_map[model](question, image_urls)
 
     sampling_params = SamplingParams(temperature=0.0,
                                      max_tokens=128,
-                                     stop_token_ids=stop_token_ids)
-    outputs = llm.chat(
+                                     stop_token_ids=req_data.stop_token_ids)
+    outputs = req_data.llm.chat(
         [{
             "role":
             "user",
@@ -203,7 +233,7 @@ def run_chat(model: str, question: str, image_urls: List[str]):
             ],
         }],
         sampling_params=sampling_params,
-        chat_template=chat_template,
+        chat_template=req_data.chat_template,
     )
 
     for o in outputs: