chore: import upstream snapshot with attribution

doc/source/serve/tutorials/video-analysis/constants.py

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+# Project constants
+
+# SigLIP model
+MODEL_NAME = "google/siglip-so400m-patch14-384"
+
+# S3 paths
+S3_VIDEOS_PREFIX = "stock-videos/"
+S3_EMBEDDINGS_PREFIX = "embeddings/"
+
+# Scene change detection
+SCENE_CHANGE_THRESHOLD = 0.15  # EMA score threshold for detecting scene changes
+EMA_ALPHA = 0.9  # EMA decay factor (higher = slower adaptation)
+
+# Pexels API
+PEXELS_API_BASE = "https://api.pexels.com/videos"
+
+# Concurrency limits
+MAX_CONCURRENT_DOWNLOADS = 5
+MAX_CONCURRENT_UPLOADS = 5
+
+# Video normalization defaults (384x384 matches model input size for fastest inference)
+NORMALIZE_WIDTH = 384
+NORMALIZE_HEIGHT = 384
+NORMALIZE_FPS = 30
+
+# Video search queries (for downloading stock videos)
+SEARCH_QUERIES = [
+    "kitchen cooking",
+    "office meeting",
+    "street city traffic",
+    "living room home",
+    "restaurant cafe",
+    "parking lot cars",
+    "classroom students",
+    "warehouse industrial",
+    "grocery store shopping",
+    "gym exercise workout",
+    "person speaking",
+    "crowd people walking",
+    "laptop computer work",
+    "outdoor nature",
+    "presentation business",
+    "conversation talking",
+    "running jogging",
+    "dining food",
+    "shopping mall",
+    "park outdoor",
+]
+
+# Video chunking defaults
+DEFAULT_NUM_FRAMES = 16
+DEFAULT_CHUNK_DURATION = 10.0
+
+# FFmpeg configuration, restricting to 2 threads to avoid over subscription.
+FFMPEG_THREADS = 6
+# Setting this to 2 because i am assuming average 
+# video length in my corpus is 20 seconds.
+# 20/10(default chunk duration) = 2
+# this means we want to set num_cpus to 4 for deployment.
+NUM_WORKERS = 3