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Updated 7 months ago

LlamaExtract

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The post describes an issue with the LlamaExtract library, where a create_schema function is raising an ApiError with a status code of 500 and the body "Internal Server Error". The community member is seeking a solution for this problem when using Pydantic models. There is one comment that mentions @Logan M, but no explicitly marked answer is provided.

jjack714_

D:\anaconda\lib\site-packages\llama_extract\base.py in acreate_schema(self, name, data_schema, project_id)
259 )
260
--> 261 response = await self._async_client.extraction.create_schema(
262 name=name, data_schema=json_schema, project_id=project_id
263 )

D:\anaconda\lib\site-packages\llama_cloud\resources\extraction\client.py in create_schema(self, name, project_id, data_schema)
468 _response_json = _response.json()
469 except JSONDecodeError:
--> 470 raise ApiError(status_code=_response.status_code, body=_response.text)
471 raise ApiError(status_code=_response.status_code, body=_response_json)
472

ApiError: status_code: 500, body: Internal Server Error

any solution for above problem LlamaExtract with Pydantic Models

1 comment

WWhiteFang_Jr

CC: @Logan M

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