Files
tabbyAPI/backends/exllamav2/vision.py
kingbri 242ff4f892 Dependencies: Fix OpenAPI generation
The vision module from the ExllamaV2 backend is used in files outside
the backends contained folder. Therefore, import ExllamaV2 as an
optional dependency here.

Signed-off-by: kingbri <bdashore3@proton.me>
2024-11-22 17:59:20 -05:00

78 lines
2.3 KiB
Python

"""Vision utilities for ExLlamaV2."""
import aiohttp
import base64
import io
import re
from async_lru import alru_cache
from fastapi import HTTPException
from PIL import Image
from common import model
from common.networking import (
handle_request_error,
)
from common.optional_dependencies import dependencies
from common.tabby_config import config
# Since this is used outside the Exl2 backend, the dependency
# may be optional
if dependencies.exllamav2:
from exllamav2.generator import ExLlamaV2MMEmbedding
async def get_image(url: str) -> Image:
if url.startswith("data:image"):
# Handle base64 image
match = re.match(r"^data:image\/[a-zA-Z0-9]+;base64,(.*)$", url)
if match:
base64_image = match.group(1)
bytes_image = base64.b64decode(base64_image)
else:
error_message = handle_request_error(
"Failed to read base64 image input.",
exc_info=False,
).error.message
raise HTTPException(400, error_message)
else:
# Handle image URL
if config.network.disable_fetch_requests:
error_message = handle_request_error(
f"Failed to fetch image from {url} as fetch requests are disabled.",
exc_info=False,
).error.message
raise HTTPException(400, error_message)
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
if response.status == 200:
bytes_image = await response.read()
else:
error_message = handle_request_error(
f"Failed to fetch image from {url}.",
exc_info=False,
).error.message
raise HTTPException(400, error_message)
return Image.open(io.BytesIO(bytes_image))
# Fetch the return type on runtime
@alru_cache(20)
async def get_image_embedding(url: str) -> "ExLlamaV2MMEmbedding":
image = await get_image(url)
return model.container.vision_model.get_image_embeddings(
model=model.container.model,
tokenizer=model.container.tokenizer,
image=image,
text_alias=None,
)
def clear_image_embedding_cache():
get_image_embedding.cache_clear()