def __init__(self, app_id=None, app_secret=None):
self._collection_id = 'hackmit'
self.request_helper = CuratorApiRequestHelper(
collection_id=self._collection_id)
super(CuratorApiClient,
self).__init__(app_id=app_id,
app_secret=app_secret,
base_url='https://api-alpha.clarifai.com',
wait_on_throttle=True)
self.add_url('document',
'curator/collections/%s/documents' % self._collection_id)
self.add_url('collections', 'curator/collections')
self.add_url('concepts', 'curator/concepts')
self.add_url('concept', 'curator/concepts/{namespace}/{cname}')
self.add_url('concept_predict',
'curator/concepts/{namespace}/{cname}/predict')
self.add_url('concept_train',
'curator/concepts/{namespace}/{cname}/train')
self.add_url('model_predict', 'curator/models/{name}/predict')
def __init__(self,
app_id='sKU_ax7BliXvEqfsutM5enhvkZ0ZSnWcnhEOuXxR',
app_secret='x-Q4HeMzasp8p153TBwgBmk0PD5QgFWnKndvtNGr'):
self._collection_id = 'hackmit'
self.request_helper = CuratorApiRequestHelper(
collection_id=self._collection_id)
super(CuratorApiClient,
self).__init__(app_id=app_id,
app_secret=app_secret,
base_url='https://api-alpha.clarifai.com',
wait_on_throttle=True)
self.add_url('document',
'curator/collections/%s/documents' % self._collection_id)
self.add_url('collections', 'curator/collections')
self.add_url('concepts', 'curator/concepts')
self.add_url('concept', 'curator/concepts/{namespace}/{cname}')
self.add_url('concept_predict',
'curator/concepts/{namespace}/{cname}/predict')
self.add_url('concept_train',
'curator/concepts/{namespace}/{cname}/train')
self.add_url('model_predict', 'curator/models/{name}/predict')
def __init__(self, app_id=None, app_secret=None):
self._collection_id = "hackmit"
self.request_helper = CuratorApiRequestHelper(collection_id=self._collection_id)
super(CuratorApiClient, self).__init__(
app_id=app_id, app_secret=app_secret, base_url="https://api-alpha.clarifai.com", wait_on_throttle=True
)
self.add_url("document", "curator/collections/%s/documents" % self._collection_id)
self.add_url("collections", "curator/collections")
self.add_url("concepts", "curator/concepts")
self.add_url("concept", "curator/concepts/{namespace}/{cname}")
self.add_url("concept_predict", "curator/concepts/{namespace}/{cname}/predict")
self.add_url("concept_train", "curator/concepts/{namespace}/{cname}/train")
self.add_url("model_predict", "curator/models/{name}/predict")
def __init__(self, app_id=None, app_secret=None):
self._collection_id = 'hackmit'
self.request_helper = CuratorApiRequestHelper(collection_id=self._collection_id)
super(CuratorApiClient, self).__init__(app_id=app_id,
app_secret=app_secret,
base_url='https://api-alpha.clarifai.com',
wait_on_throttle=True)
self.add_url('document', 'curator/collections/%s/documents' % self._collection_id)
self.add_url('collections', 'curator/collections')
self.add_url('concepts', 'curator/concepts')
self.add_url('concept', 'curator/concepts/{namespace}/{cname}')
self.add_url('concept_predict', 'curator/concepts/{namespace}/{cname}/predict')
self.add_url('concept_train', 'curator/concepts/{namespace}/{cname}/train')
def __init__(self, app_id='sKU_ax7BliXvEqfsutM5enhvkZ0ZSnWcnhEOuXxR', app_secret='x-Q4HeMzasp8p153TBwgBmk0PD5QgFWnKndvtNGr'):
self._collection_id = 'hackmit'
self.request_helper = CuratorApiRequestHelper(collection_id=self._collection_id)
super(CuratorApiClient, self).__init__(app_id=app_id,
app_secret=app_secret,
base_url='https://api-alpha.clarifai.com',
wait_on_throttle=True)
self.add_url('document', 'curator/collections/%s/documents' % self._collection_id)
self.add_url('collections', 'curator/collections')
self.add_url('concepts', 'curator/concepts')
self.add_url('concept', 'curator/concepts/{namespace}/{cname}')
self.add_url('concept_predict', 'curator/concepts/{namespace}/{cname}/predict')
self.add_url('concept_train', 'curator/concepts/{namespace}/{cname}/train')
self.add_url('model_predict', 'curator/models/{name}/predict')
class CuratorApiClient(ClarifaiApi):
def __init__(self, app_id=None, app_secret=None):
self._collection_id = 'hackmit'
self.request_helper = CuratorApiRequestHelper(collection_id=self._collection_id)
super(CuratorApiClient, self).__init__(app_id=app_id,
app_secret=app_secret,
base_url='https://api-alpha.clarifai.com',
wait_on_throttle=True)
self.add_url('document', 'curator/collections/%s/documents' % self._collection_id)
self.add_url('collections', 'curator/collections')
self.add_url('concepts', 'curator/concepts')
self.add_url('concept', 'curator/concepts/{namespace}/{cname}')
self.add_url('concept_predict', 'curator/concepts/{namespace}/{cname}/predict')
self.add_url('concept_train', 'curator/concepts/{namespace}/{cname}/train')
self.add_url('model_predict', 'curator/models/{name}/predict')
def add_url(self, op, path):
self._urls[op] = '/'.join([self._base_url, API_VERSION, path])
def check_status(self, raw_response):
response = json.loads(raw_response.decode("utf-8"))
try:
ok = (response['status']['status'] == 'OK')
except:
raise ApiError('Malformed API response.')
if not ok:
raise CuratorApiError(response['status'])
return response
def add_document(self, doc, options=None):
docid = doc.get('docid')
if not docid:
raise ApiBadRequestError('Missing required param: doc.docid')
url = self._url_for_op('document')
request_data = self.request_helper.document_request_for_put(doc, options=options)
kwargs = {
'data': request_data,
'method': 'POST'
}
raw_response = self._get_raw_response(self._get_json_headers,
self._get_json_response,
url,
kwargs)
return self.check_status(raw_response)
def create_collection(self, settings, properties=None):
url = self._url_for_op('collections')
request_data = self.request_helper.index_request_for_put(settings, properties=properties)
kwargs = {
'data': request_data,
'method': 'POST'
}
raw_response = self._get_raw_response(self._get_json_headers,
self._get_json_response,
url, kwargs)
return self.check_status(raw_response)
@request('concepts', method='POST')
def create_concept(self, namespace, cname, description=None, example=None, **kwargs):
"""
Create a new concept
Args:
namespace: namespace for the concept
cname: name of the concept
description (Optional): description of the concept
example (Optional): image url with an example of the concept
"""
return drop({
'namespace': namespace,
'cname': cname,
'description': description,
'example': example
}, value=None)
@request('concept_train', method='POST')
def train_concept(self, namespace, cname, collection_ids=None):
if not re.match(r'^[A-Za-z0-09-_]+$', cname):
raise ApiError('Concept name cannot contain whitespace or punctuation: "%s"' % cname)
if collection_ids:
return {'collection_ids': collection_ids}
@request('concept_predict', method='POST')
def predict_concept(self, namespace, cname, urls=None, documents=None):
'''
Predict scores for a single concept, specified by namespace and cname.
'''
return drop({
'urls': urls,
'documents': documents
}, value=None)
@request('model_predict', method='POST')
def predict_model(self, name, urls=None, documents=None):
'''
Predict tags for the urls.
Args:
model_name:
Namespace or model name. This will return predictions for all concepts
in the model. If a namespace, uses all concepts in the namespace.
urls:
List of urls to find tag predictions.
'''
return drop({
'urls': urls,
'documents': documents
}, value=None)
class CuratorApiClient(ClarifaiApi):
def __init__(self,
app_id='sKU_ax7BliXvEqfsutM5enhvkZ0ZSnWcnhEOuXxR',
app_secret='x-Q4HeMzasp8p153TBwgBmk0PD5QgFWnKndvtNGr'):
self._collection_id = 'hackmit'
self.request_helper = CuratorApiRequestHelper(
collection_id=self._collection_id)
super(CuratorApiClient,
self).__init__(app_id=app_id,
app_secret=app_secret,
base_url='https://api-alpha.clarifai.com',
wait_on_throttle=True)
self.add_url('document',
'curator/collections/%s/documents' % self._collection_id)
self.add_url('collections', 'curator/collections')
self.add_url('concepts', 'curator/concepts')
self.add_url('concept', 'curator/concepts/{namespace}/{cname}')
self.add_url('concept_predict',
'curator/concepts/{namespace}/{cname}/predict')
self.add_url('concept_train',
'curator/concepts/{namespace}/{cname}/train')
self.add_url('model_predict', 'curator/models/{name}/predict')
def add_url(self, op, path):
self._urls[op] = '/'.join([self._base_url, API_VERSION, path])
def check_status(self, raw_response):
response = json.loads(raw_response)
try:
ok = (response['status']['status'] == 'OK')
except:
raise ApiError('Malformed API response.')
if not ok:
raise CuratorApiError(response['status'])
return response
def add_document(self, doc, options=None):
docid = doc.get('docid')
if not docid:
raise ApiBadRequestError('Missing required param: doc.docid')
url = self._url_for_op('document')
request_data = self.request_helper.document_request_for_put(
doc, options=options)
kwargs = {'data': request_data, 'method': 'POST'}
raw_response = self._get_raw_response(self._get_json_headers,
self._get_json_response, url,
kwargs)
return self.check_status(raw_response)
def create_collection(self, settings, properties=None):
url = self._url_for_op('collections')
request_data = self.request_helper.index_request_for_put(
settings, properties=properties)
kwargs = {'data': request_data, 'method': 'POST'}
raw_response = self._get_raw_response(self._get_json_headers,
self._get_json_response, url,
kwargs)
return self.check_status(raw_response)
@request('concepts', method='POST')
def create_concept(self,
namespace,
cname,
description=None,
example=None,
**kwargs):
"""
Create a new concept
Args:
namespace: namespace for the concept
cname: name of the concept
description (Optional): description of the concept
example (Optional): image url with an example of the concept
"""
return drop(
{
'namespace': namespace,
'cname': cname,
'description': description,
'example': example
},
value=None)
@request('concept_train', method='POST')
def train_concept(self, namespace, cname, collection_ids=None):
if not re.match(r'^[A-Za-z0-09-_]+$', cname):
raise ApiError(
'Concept name cannot contain whitespace or punctuation: "%s"' %
cname)
if collection_ids:
return {'collection_ids': collection_ids}
@request('concept_predict', method='POST')
def predict_concept(self, namespace, cname, urls=None, documents=None):
'''
Predict scores for a single concept, specified by namespace and cname.
'''
return drop({'urls': urls, 'documents': documents}, value=None)
@request('model_predict', method='POST')
def predict_model(self, name, urls=None, documents=None):
'''
Predict tags for the urls.
Args:
model_name:
Namespace or model name. This will return predictions for all concepts
in the model. If a namespace, uses all concepts in the namespace.
urls:
List of urls to find tag predictions.
'''
return drop({'urls': urls, 'documents': documents}, value=None)
class CuratorApiClient(ClarifaiApi):
def __init__(self, app_id=None, app_secret=None):
self._collection_id = "hackmit"
self.request_helper = CuratorApiRequestHelper(collection_id=self._collection_id)
super(CuratorApiClient, self).__init__(
app_id=app_id, app_secret=app_secret, base_url="https://api-alpha.clarifai.com", wait_on_throttle=True
)
self.add_url("document", "curator/collections/%s/documents" % self._collection_id)
self.add_url("collections", "curator/collections")
self.add_url("concepts", "curator/concepts")
self.add_url("concept", "curator/concepts/{namespace}/{cname}")
self.add_url("concept_predict", "curator/concepts/{namespace}/{cname}/predict")
self.add_url("concept_train", "curator/concepts/{namespace}/{cname}/train")
self.add_url("model_predict", "curator/models/{name}/predict")
def add_url(self, op, path):
self._urls[op] = "/".join([self._base_url, API_VERSION, path])
def check_status(self, raw_response):
############################################################################
raw_response = raw_response.decode("utf-8")
############################################################################
response = json.loads(raw_response)
try:
ok = response["status"]["status"] == "OK"
except:
raise ApiError("Malformed API response.")
if not ok:
raise CuratorApiError(response["status"])
return response
def add_document(self, doc, options=None):
docid = doc.get("docid")
if not docid:
raise ApiBadRequestError("Missing required param: doc.docid")
url = self._url_for_op("document")
request_data = self.request_helper.document_request_for_put(doc, options=options)
kwargs = {"data": request_data, "method": "POST"}
raw_response = self._get_raw_response(self._get_json_headers, self._get_json_response, url, kwargs)
return self.check_status(raw_response)
def create_collection(self, settings, properties=None):
url = self._url_for_op("collections")
request_data = self.request_helper.index_request_for_put(settings, properties=properties)
kwargs = {"data": request_data, "method": "POST"}
raw_response = self._get_raw_response(self._get_json_headers, self._get_json_response, url, kwargs)
return self.check_status(raw_response)
@request("concepts", method="POST")
def create_concept(self, namespace, cname, description=None, example=None, **kwargs):
"""
Create a new concept
Args:
namespace: namespace for the concept
cname: name of the concept
description (Optional): description of the concept
example (Optional): image url with an example of the concept
"""
return drop(
{"namespace": namespace, "cname": cname, "description": description, "example": example}, value=None
)
@request("concept_train", method="POST")
def train_concept(self, namespace, cname, collection_ids=None):
if not re.match(r"^[A-Za-z0-09-_]+$", cname):
raise ApiError('Concept name cannot contain whitespace or punctuation: "%s"' % cname)
if collection_ids:
return {"collection_ids": collection_ids}
@request("concept_predict", method="POST")
def predict_concept(self, namespace, cname, urls=None, documents=None):
"""
Predict scores for a single concept, specified by namespace and cname.
"""
return drop({"urls": urls, "documents": documents}, value=None)
@request("model_predict", method="POST")
def predict_model(self, name, urls=None, documents=None):
"""
Predict tags for the urls.
Args:
model_name:
Namespace or model name. This will return predictions for all concepts
in the model. If a namespace, uses all concepts in the namespace.
urls:
List of urls to find tag predictions.
"""
return drop({"urls": urls, "documents": documents}, value=None)
