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d57be47b0f
* ci(config.yml): add a 'check_code_quality' step Addresses https://github.com/BerriAI/litellm/issues/5991 * ci(config.yml): check why circle ci doesn't pick up this test * ci(config.yml): fix to run 'check_code_quality' tests * fix(__init__.py): fix unprotected import * fix(__init__.py): don't remove unused imports * build(ruff.toml): update ruff.toml to ignore unused imports * fix: fix: ruff + pyright - fix linting + type-checking errors * fix: fix linting errors * fix(lago.py): fix module init error * fix: fix linting errors * ci(config.yml): cd into correct dir for checks * fix(proxy_server.py): fix linting error * fix(utils.py): fix bare except causes ruff linting errors * fix: ruff - fix remaining linting errors * fix(clickhouse.py): use standard logging object * fix(__init__.py): fix unprotected import * fix: ruff - fix linting errors * fix: fix linting errors * ci(config.yml): cleanup code qa step (formatting handled in local_testing) * fix(_health_endpoints.py): fix ruff linting errors * ci(config.yml): just use ruff in check_code_quality pipeline for now * build(custom_guardrail.py): include missing file * style(embedding_handler.py): fix ruff check
87 lines
2.5 KiB
Python
87 lines
2.5 KiB
Python
"""
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Helper functions to handle images passed in messages
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"""
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import base64
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from httpx import Response
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import litellm
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from litellm import verbose_logger
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from litellm.caching import InMemoryCache
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from litellm.llms.custom_httpx.http_handler import (
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_get_httpx_client,
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get_async_httpx_client,
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)
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MAX_IMGS_IN_MEMORY = 10
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in_memory_cache = InMemoryCache(max_size_in_memory=MAX_IMGS_IN_MEMORY)
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def _process_image_response(response: Response, url: str) -> str:
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if response.status_code != 200:
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raise Exception(
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f"Error: Unable to fetch image from URL. Status code: {response.status_code}, url={url}"
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)
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image_bytes = response.content
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base64_image = base64.b64encode(image_bytes).decode("utf-8")
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image_type = response.headers.get("Content-Type")
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if image_type is None:
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img_type = url.split(".")[-1].lower()
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_img_type = {
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"jpg": "image/jpeg",
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"jpeg": "image/jpeg",
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"png": "image/png",
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"gif": "image/gif",
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"webp": "image/webp",
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}.get(img_type)
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if _img_type is None:
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raise Exception(
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f"Error: Unsupported image format. Format={_img_type}. Supported types = ['image/jpeg', 'image/png', 'image/gif', 'image/webp']"
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)
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img_type = _img_type
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else:
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img_type = image_type
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result = f"data:{img_type};base64,{base64_image}"
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in_memory_cache.set_cache(url, result)
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return result
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async def async_convert_url_to_base64(url: str) -> str:
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cached_result = in_memory_cache.get_cache(url)
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if cached_result:
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return cached_result
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client = litellm.module_level_aclient
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for _ in range(3):
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try:
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response = await client.get(url, follow_redirects=True)
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return _process_image_response(response, url)
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except Exception:
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pass
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raise Exception(
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f"Error: Unable to fetch image from URL after 3 attempts. url={url}"
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)
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def convert_url_to_base64(url: str) -> str:
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cached_result = in_memory_cache.get_cache(url)
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if cached_result:
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return cached_result
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client = litellm.module_level_client
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for _ in range(3):
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try:
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response = client.get(url, follow_redirects=True)
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return _process_image_response(response, url)
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except Exception as e:
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verbose_logger.exception(e)
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# print(e)
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pass
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raise Exception(
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f"Error: Unable to fetch image from URL after 3 attempts. url={url}"
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)
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