mirror of
https://github.com/BerriAI/litellm.git
synced 2026-09-15 23:31:29 +00:00
347b642bdd
* refactor(ocr): extract call completion boundary * fix(ocr): release completion state after dispatch * test(ocr): prove wrapper completion handoff * test(ocr): narrow mapped failure assertion * fix(ocr): preserve wrapper invocation kwargs * fix(ocr): retain completion through finalization * fix(ocr): make completion ownership explicit * refactor(ocr): resolve logging executor explicitly * fix(callbacks): preserve completion lifecycle behavior * refactor(ocr): move public OCR into native lifecycle * refactor(ocr): remove unused rust bridge capability * wip * wip * refactor * wip * fix(ocr): preserve reducto native compatibility * wip * fix(ocr): document native callable casts * perf(ocr): bound responses and reduce native scheduling overhead * refactor(python-bridge): organize placeholder routes * refactor test * fix(ocr): normalize DeepSeek document content * perf(ocr): skip unused callback work and benchmark callback overhead * fix(ocr): align conversion contracts * test(ocr): cover official provider response shapes * fix(ocr): restore Python fallback and honor Rust opt-out * fixes and refactor * fix(ocr): preserve Azure Document Intelligence authentication * fix(rust): enforce OCR response limits and lint contracts * test(rust): align native OCR contract coverage * test(ocr): isolate Azure auth precedence coverage
58 lines
2 KiB
Python
58 lines
2 KiB
Python
from typing import Final
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import litellm
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from litellm.llms.base_llm.ocr.transformation import OCRResponse
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from tests.test_litellm_rust.support.recording_server import RecordingServer
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OCR_DOCUMENT: Final = {"type": "document_url", "document_url": "data:application/pdf;base64,YWJj"}
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OCR_MODEL: Final = "mistral/mistral-ocr-latest"
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OCR_RESPONSE: Final = {
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"pages": [{"index": 0, "markdown": "native OCR response", "images": [], "dimensions": None}],
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"model": "mistral-ocr-latest",
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"usage_info": {"pages_processed": 1, "doc_size_bytes": 3},
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}
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def ocr_arguments(server: RecordingServer, **kwargs: object) -> dict[str, object]:
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return {
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"model": OCR_MODEL,
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"document": dict(OCR_DOCUMENT),
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"api_key": "test-key",
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"api_base": server.base_url,
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**kwargs,
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}
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def call_ocr(server: RecordingServer, **kwargs: object) -> OCRResponse:
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response: Final = litellm.ocr(**ocr_arguments(server, **kwargs))
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if not isinstance(response, OCRResponse):
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raise TypeError(f"Expected OCRResponse, got {type(response).__name__}")
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return response
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async def call_aocr(server: RecordingServer, **kwargs: object) -> OCRResponse:
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return await litellm.aocr(**ocr_arguments(server, **kwargs))
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def call_native_ocr(server: RecordingServer, **kwargs: object) -> OCRResponse:
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return call_ocr(server, **kwargs)
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async def call_native_aocr(server: RecordingServer, **kwargs: object) -> OCRResponse:
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return await call_aocr(server, **kwargs)
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def request_body(kwargs: dict[str, object]) -> dict[str, object]:
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additional_args = kwargs["additional_args"]
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assert isinstance(additional_args, dict)
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body = additional_args["complete_input_dict"]
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assert isinstance(body, dict)
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return body
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def request_headers(kwargs: dict[str, object]) -> dict[str, object]:
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additional_args = kwargs["additional_args"]
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assert isinstance(additional_args, dict)
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headers = additional_args["headers"]
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assert isinstance(headers, dict)
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return headers
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