downloading videos

server/text_generation_server/models/vlm_causal_lm.py

@@ -1,7 +1,9 @@
 import torch
+import requests
 from PIL import Image
 from io import BytesIO
 
+from contextlib import contextmanager
 from opentelemetry import trace
 from typing import Iterable, Optional, Tuple, List, Type, Dict
 
@@ -218,8 +220,10 @@ class VlmCausalLMBatch(FlashCausalLMBatch):
                     )
                     image_id += 1
                 elif chunk_type == "video" and config.model_type == "qwen2_vl":
-                    # Based on Qwen2VL's video token format
-                    full_text += f"<video>{chunk.video}</video>"
+                    # Download and process video in a temporary context
+                    with cls.temp_video_download(chunk.video) as local_path:
+                        # Now the video is available at local_path for processing
+                        full_text += f"<video>{local_path}</video>"
 
             full_text = image_text_replacement_fixup(config, full_text)
 
@@ -272,6 +276,26 @@ class VlmCausalLMBatch(FlashCausalLMBatch):
             batch.image_grid_thw = None
         return batch
     
+    @staticmethod
+    @contextmanager
+    def temp_video_download(url: str) -> str:
+        """Downloads video to a temporary file and cleans it up after use."""
+        with tempfile.NamedTemporaryFile(suffix=os.path.splitext(url)[1], delete=False) as tmp_file:
+            try:
+                # Download video
+                with requests.get(url, stream=True) as r:
+                    r.raise_for_status()
+                    for chunk in r.iter_content(chunk_size=8192):
+                        if chunk:
+                            tmp_file.write(chunk)
+                tmp_file.flush()
+                yield tmp_file.name
+            finally:
+                # Clean up temp file
+                try:
+                    os.unlink(tmp_file.name)
+                except OSError:
+                    pass
 
 class VlmCausalLM(FlashCausalLM):
     def __init__(