Stanislav Hejny
78 lines
4.1 KiB
Python
78 lines
4.1 KiB
Python
import logging
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from fastapi import APIRouter, status, Depends
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from fastapi import Path as FPath
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from fastapi import UploadFile
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from cleverswarm.schemas.user_schema import UserSchema
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from cleverswarm.schemas.job_id_schema import JobIdSchema
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from cleverswarm.core.deps import get_current_user
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logger = logging.getLogger('Unstructured')
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# Enable propagation to the root logger
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logger.propagate = True
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router = APIRouter()
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# POST Convert
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@router.post('/with_ontology', status_code=status.HTTP_201_CREATED, summary='Convert unstructured text to KG',
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description='Converts unstructured text to a Knowledge Graph according to the provided ontology',
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response_description='Returns the Job/Request ID for reference in future interactions',
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responses={
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200: {'model': JobIdSchema,
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'description': 'The KG extraction job ID'},
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400: {'description': 'Input parameters are not compliant with request'},
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500: {'description': 'A server error occurred while processing the request'}
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})
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async def create_extract_with_ontology(unstructured: UploadFile,
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ontology: UploadFile,
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ontology_spec: UploadFile,
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authenticated_user: UserSchema = Depends(get_current_user)):
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logger.debug('====> POST /unstructured/with_ontology: Started convertToKG')
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logger.debug('====> arguments: unstructured=%s, ontology=%s, ontology_spec=%s', unstructured, ontology, ontology_spec)
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return JobIdSchema(job_id='123456-TestKG')
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# POST Convert
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@router.post('/with_wildcards', status_code=status.HTTP_201_CREATED,
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summary='Convert unstructured text to KG with Wildcards filtering',
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description='Converts unstructured text to a Knowledge Graph according to the provided ontology, while'
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'applying a filtering based on the Wildcards ontology',
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response_description='Knowledge Graph defined by RDF triplets in JSON format',
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responses={
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200: {'model': JobIdSchema,
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'description': 'The KG extraction job ID'},
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400: {'description': 'Input parameters are not compliant with request'},
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500: {'description': 'A server error occurred while processing the request'}
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})
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async def create_extract_with_ontology(unstructured: UploadFile,
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ontology: UploadFile,
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ontology_spec: UploadFile,
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wildcards: UploadFile,
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authenticated_user: UserSchema = Depends(get_current_user)):
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logger.debug('====> POST /unstructured/with_wildcards: Started convertToKG with Wildcards filtering')
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logger.debug('====> arguments: unstructured=%s, ontology=%s, ontology_spec=%s, wildcards=%s',
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unstructured, ontology, ontology_spec, wildcards)
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return JobIdSchema(job_id='123456-TestKG')
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@router.get('/{request_id}', summary='Polls or Retrieves a KG by id',
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description='Polls or Retrieves a processed KG by id. If the KG is not ready yet it sends a '
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'NO CONTENT (204) HTTP status',
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response_description='Response is in the form of json data',
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responses={
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200: {'description': 'The KG extracted data'},
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204: {'description': 'Job is not completed yet'},
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404: {'description': 'Job ID not found'},
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412: {'description': 'Job does not correspond to a KG extraction job'},
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500: {'description': 'A server error occurred while processing the request'}
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})
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async def get_kg(request_id: str = FPath(title='The job id',
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description='The id of the job for which the results are to be retrieved'),
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authenticated_user: UserSchema = Depends(get_current_user)):
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logger.debug(f'====> GET /unstructured/{request_id}: Started convertToKG with Wildcards filtering')
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