[Fix] Fix llava on multi images (#1247)

python/sglang/srt/utils.py

@@ -26,7 +26,7 @@ import struct
 import time
 from importlib.metadata import PackageNotFoundError, version
 from io import BytesIO
-from typing import List, Optional
+from typing import List, Optional, Union
 
 import numpy as np
 import psutil
@@ -193,35 +193,16 @@ def allocate_init_ports(
     return ret_ports[0], ret_ports[1:num_ports_needed]
 
 
-def get_int_token_logit_bias(tokenizer, vocab_size):
-    """Get the logit bias for integer-only tokens."""
-    # a bug when model's vocab size > tokenizer.vocab_size
-    if tokenizer == None:
-        return [-1e5] * vocab_size
-    vocab_size = tokenizer.vocab_size
-    logit_bias = np.zeros(vocab_size, dtype=np.float32)
-    for t_id in range(vocab_size):
-        ss = tokenizer.decode([t_id]).strip()
-        if not (ss.isdigit() or len(ss) == 0 or t_id == tokenizer.eos_token_id):
-            logit_bias[t_id] = -1e5
-
-    return logit_bias
-
-
-def is_multimodal_model(model):
-    from sglang.srt.model_config import ModelConfig
-
-    if isinstance(model, str):
-        model = model.lower()
-        return "llava" in model or "yi-vl" in model or "llava-next" in model
-
-    if isinstance(model, ModelConfig):
-        model_path = model.path.lower()
-        return (
-            "llava" in model_path or "yi-vl" in model_path or "llava-next" in model_path
-        )
-
-    raise ValueError("unrecognized type")
+def is_multimodal_model(model_architectures):
+    if (
+        "LlavaLlamaForCausalLM" in model_architectures
+        or "LlavaQwenForCausalLM" in model_architectures
+        or "LlavaMistralForCausalLM" in model_architectures
+        or "LlavaVidForCausalLM" in model_architectures
+    ):
+        return True
+    else:
+        return False
 
 
 def is_generation_model(model_architectures, is_embedding: bool = False):
@@ -317,12 +298,14 @@ def decode_video_base64(video_base64):
         )  # Return an empty array and size tuple if no frames were found
 
 
-def load_image(image_file):
+def load_image(image_file: Union[str, bytes]):
     from PIL import Image
 
     image = image_size = None
 
-    if image_file.startswith("http://") or image_file.startswith("https://"):
+    if isinstance(image_file, bytes):
+        image = Image.open(BytesIO(image_file))
+    elif image_file.startswith("http://") or image_file.startswith("https://"):
         timeout = int(os.getenv("REQUEST_TIMEOUT", "3"))
         response = requests.get(image_file, timeout=timeout)
         image = Image.open(BytesIO(response.content))
@@ -334,8 +317,10 @@ def load_image(image_file):
     elif image_file.startswith("video:"):
         image_file = image_file.replace("video:", "")
         image, image_size = decode_video_base64(image_file)
-    else:
+    elif isinstance(image_file, str):
         image = Image.open(BytesIO(base64.b64decode(image_file)))
+    else:
+        raise ValueError(f"Invalid image: {image}")
 
     return image, image_size