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feat: supported multi-modal embeddings from Azure AI Vision service (#…
…162)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,86 @@ | ||
| from typing import ( | ||
| Any, | ||
| AsyncIterator, | ||
| Callable, | ||
| Coroutine, | ||
| List, | ||
| TypeVar, | ||
| assert_never, | ||
| cast, | ||
| ) | ||
|
|
||
| from aidial_sdk.chat_completion.request import Attachment | ||
| from aidial_sdk.embeddings.request import EmbeddingsRequest | ||
| from aidial_sdk.exceptions import RequestValidationError | ||
|
|
||
| _T = TypeVar("_T") | ||
|
|
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| _Coro = Coroutine[_T, Any, Any] | ||
| _Tokens = List[int] | ||
|
|
||
|
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| async def reject_tokens(tokens: _Tokens): | ||
| raise RequestValidationError( | ||
| "Tokens in an embedding input are not supported. Provide text instead. " | ||
| "When Langchain AzureOpenAIEmbeddings class is used, set 'check_embedding_ctx_length=False' to disable tokenization." | ||
| ) | ||
|
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||
|
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| async def reject_mixed(input: List[str | Attachment]): | ||
| raise RequestValidationError( | ||
| "Embedding inputs composed of multiple texts and/or attachments aren't supported" | ||
| ) | ||
|
|
||
|
|
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| async def collect_embedding_inputs( | ||
| request: EmbeddingsRequest, | ||
| *, | ||
| on_text: Callable[[str], _Coro[_T]], | ||
| on_attachment: Callable[[Attachment], _Coro[_T]], | ||
| on_tokens: Callable[[_Tokens], _Coro[_T]] = reject_tokens, | ||
| on_mixed: Callable[[List[str | Attachment]], _Coro[_T]] = reject_mixed, | ||
| ) -> AsyncIterator[_T]: | ||
|
|
||
| async def _on_str_or_attachment(input: str | Attachment) -> _T: | ||
| if isinstance(input, str): | ||
| return await on_text(input) | ||
| elif isinstance(input, Attachment): | ||
| return await on_attachment(input) | ||
| else: | ||
| assert_never(input) | ||
|
|
||
| if isinstance(request.input, str): | ||
| yield await on_text(request.input) | ||
| elif isinstance(request.input, list): | ||
|
|
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| is_list_of_tokens = False | ||
| for input in request.input: | ||
| if isinstance(input, str): | ||
| yield await on_text(input) | ||
| elif isinstance(input, list): | ||
| yield await on_tokens(input) | ||
| else: | ||
| is_list_of_tokens = True | ||
| break | ||
|
|
||
| if is_list_of_tokens: | ||
| yield await on_tokens(cast(_Tokens, request.input)) | ||
|
|
||
| else: | ||
| assert_never(request.input) | ||
|
|
||
| if request.custom_input is None: | ||
| return | ||
|
|
||
| for input in request.custom_input: | ||
| if isinstance(input, (str, Attachment)): | ||
| yield await _on_str_or_attachment(input) | ||
| elif isinstance(input, list): | ||
| if len(input) == 0: | ||
| pass | ||
| elif len(input) == 1: | ||
| yield await _on_str_or_attachment(input[0]) | ||
| else: | ||
| yield await on_mixed(input) | ||
| else: | ||
| assert_never(input) |
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