mirror of
https://github.com/theroyallab/tabbyAPI.git
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dd41eec8a4
* Support image_url inputs containing URLs or base64 strings following OAI vision spec * Use async lru cache for image embeddings * Add generic wrapper class for multimodal embeddings
62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
"""Vision utilities for ExLlamaV2."""
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import io
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import base64
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import re
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from PIL import Image
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from common import model
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import aiohttp
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from common.networking import (
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handle_request_error,
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)
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from fastapi import HTTPException
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from exllamav2.generator import ExLlamaV2MMEmbedding
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from async_lru import alru_cache
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async def get_image(url: str) -> Image:
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if url.startswith("data:image"):
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# Handle base64 image
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match = re.match(r"^data:image\/[a-zA-Z0-9]+;base64,(.*)$", url)
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if match:
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base64_image = match.group(1)
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bytes_image = base64.b64decode(base64_image)
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else:
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error_message = handle_request_error(
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"Failed to read base64 image input.",
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exc_info=False,
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).error.message
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raise HTTPException(400, error_message)
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else:
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# Handle image URL
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async with aiohttp.ClientSession() as session:
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async with session.get(url) as response:
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if response.status == 200:
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bytes_image = await response.read()
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else:
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error_message = handle_request_error(
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f"Failed to fetch image from {url}.",
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exc_info=False,
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).error.message
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raise HTTPException(400, error_message)
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return Image.open(io.BytesIO(bytes_image))
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@alru_cache(20)
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async def get_image_embedding(url: str) -> ExLlamaV2MMEmbedding:
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image = await get_image(url)
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return model.container.vision_model.get_image_embeddings(
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model=model.container.model,
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tokenizer=model.container.tokenizer,
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image=image,
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text_alias=None,
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)
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def clear_image_embedding_cache():
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get_image_embedding.cache_clear()
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