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Support 'file' message type for VLLM video url's + Anthropic redacted message thinking support (#10129)
* feat(hosted_vllm/chat/transformation.py): support calling vllm video url with openai 'file' message type allows switching between gemini/vllm easily * [WIP] redacted thinking tests (#9044) * WIP: redacted thinking tests * test: add test for redacted thinking in assistant message --------- Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com> * fix(anthropic/chat/transformation.py): support redacted thinking block on anthropic completion Fixes https://github.com/BerriAI/litellm/issues/9058 * fix(anthropic/chat/handler.py): transform anthropic redacted messages on streaming Fixes https://github.com/BerriAI/litellm/issues/9058 * fix(bedrock/): support redacted text on streaming + non-streaming Fixes https://github.com/BerriAI/litellm/issues/9058 * feat(litellm_proxy/chat/transformation.py): support 'reasoning_effort' param for proxy allows using reasoning effort with thinking models on proxy * test: update tests * fix(utils.py): fix linting error * fix: fix linting errors * fix: fix linting errors * fix: fix linting error * fix: fix linting errors * fix(anthropic/chat/transformation.py): fix returning citations in chat completion --------- Co-authored-by: Johann Miller <22018973+johannkm@users.noreply.github.com>
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20 changed files with 638 additions and 109 deletions
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@ -14,6 +14,7 @@ from litellm.types.llms.openai import ChatCompletionThinkingBlock
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from litellm.types.utils import (
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ChatCompletionDeltaToolCall,
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ChatCompletionMessageToolCall,
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ChatCompletionRedactedThinkingBlock,
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Choices,
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Delta,
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EmbeddingResponse,
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@ -486,7 +487,14 @@ def convert_to_model_response_object( # noqa: PLR0915
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)
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# Handle thinking models that display `thinking_blocks` within `content`
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thinking_blocks: Optional[List[ChatCompletionThinkingBlock]] = None
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thinking_blocks: Optional[
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List[
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Union[
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ChatCompletionThinkingBlock,
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ChatCompletionRedactedThinkingBlock,
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]
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]
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] = None
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if "thinking_blocks" in choice["message"]:
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thinking_blocks = choice["message"]["thinking_blocks"]
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provider_specific_fields["thinking_blocks"] = thinking_blocks
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@ -471,3 +471,59 @@ def unpack_defs(schema, defs):
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unpack_defs(ref, defs)
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value["items"] = ref
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continue
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def _get_image_mime_type_from_url(url: str) -> Optional[str]:
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"""
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Get mime type for common image URLs
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See gemini mime types: https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/image-understanding#image-requirements
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Supported by Gemini:
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application/pdf
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audio/mpeg
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audio/mp3
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audio/wav
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image/png
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image/jpeg
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image/webp
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text/plain
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video/mov
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video/mpeg
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video/mp4
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video/mpg
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video/avi
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video/wmv
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video/mpegps
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video/flv
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"""
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url = url.lower()
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# Map file extensions to mime types
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mime_types = {
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# Images
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(".jpg", ".jpeg"): "image/jpeg",
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(".png",): "image/png",
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(".webp",): "image/webp",
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# Videos
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(".mp4",): "video/mp4",
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(".mov",): "video/mov",
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(".mpeg", ".mpg"): "video/mpeg",
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(".avi",): "video/avi",
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(".wmv",): "video/wmv",
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(".mpegps",): "video/mpegps",
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(".flv",): "video/flv",
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# Audio
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(".mp3",): "audio/mp3",
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(".wav",): "audio/wav",
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(".mpeg",): "audio/mpeg",
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# Documents
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(".pdf",): "application/pdf",
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(".txt",): "text/plain",
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}
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# Check each extension group against the URL
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for extensions, mime_type in mime_types.items():
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if any(url.endswith(ext) for ext in extensions):
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return mime_type
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return None
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@ -2258,6 +2258,14 @@ def _parse_content_type(content_type: str) -> str:
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return m.get_content_type()
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def _parse_mime_type(base64_data: str) -> Optional[str]:
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mime_type_match = re.match(r"data:(.*?);base64", base64_data)
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if mime_type_match:
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return mime_type_match.group(1)
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else:
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return None
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class BedrockImageProcessor:
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"""Handles both sync and async image processing for Bedrock conversations."""
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