67 lines
2.1 KiB
Python
67 lines
2.1 KiB
Python
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"""Image and timestamp helpers used by the Ollama/OpenAI request pipeline."""
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import base64
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import io
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import time
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from datetime import datetime, timezone
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from PIL import Image
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def iso8601_ns():
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ns = time.time_ns()
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sec, ns_rem = divmod(ns, 1_000_000_000)
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dt = datetime.fromtimestamp(sec, tz=timezone.utc)
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return (
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f"{dt.year:04d}-{dt.month:02d}-{dt.day:02d}T"
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f"{dt.hour:02d}:{dt.minute:02d}:{dt.second:02d}."
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f"{ns_rem:09d}Z"
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)
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def is_base64(image_string):
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try:
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if isinstance(image_string, str) and base64.b64encode(base64.b64decode(image_string)) == image_string.encode():
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return True
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except Exception:
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return False
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def resize_image_if_needed(image_data):
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try:
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# Check if already data-url
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if image_data.startswith("data:"):
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try:
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header, image_data = image_data.split(",", 1)
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except ValueError:
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pass
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# Decode the base64 image data
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image_bytes = base64.b64decode(image_data)
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with Image.open(io.BytesIO(image_bytes)) as image:
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if image.mode not in ("RGB", "L"):
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image = image.convert("RGB")
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# Get current size
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width, height = image.size
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# Calculate the new dimensions while maintaining aspect ratio
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if width > 512 or height > 512:
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aspect_ratio = width / height
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if aspect_ratio > 1: # Width is larger
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new_width = 512
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new_height = int(512 / aspect_ratio)
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else: # Height is larger
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new_height = 512
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new_width = int(512 * aspect_ratio)
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image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
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# Encode the resized image back to base64
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buffered = io.BytesIO()
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image.save(buffered, format="PNG")
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resized_image_data = base64.b64encode(buffered.getvalue()).decode("utf-8")
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return resized_image_data
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except Exception as e:
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print(f"Error processing image: {e}")
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return None
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