def from_http_request(self, req: HTTPRequest) -> MultiImgTask:
if len(self.input_names) == 1:
# broad parsing while single input
if req.parsed_headers.content_type == 'multipart/form-data':
_, _, files = HTTPRequest.parse_form_data(req)
if not any(files):
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=
f"BentoML#{self.__class__.__name__} requires inputs"
f"fields {self.input_names}",
)
else:
f = next(iter(files.values()))
task = InferenceTask(
context=InferenceContext(
http_headers=req.parsed_headers),
data=(f, ),
)
else:
# for images/*
task = InferenceTask(
context=InferenceContext(http_headers=req.parsed_headers),
data=(io.BytesIO(req.body), ),
)
elif req.parsed_headers.content_type == 'multipart/form-data':
_, _, files = HTTPRequest.parse_form_data(req)
files = tuple(files.get(k) for k in self.input_names)
if not any(files):
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=f"BentoML#{self.__class__.__name__} requires inputs "
f"fields {self.input_names}",
)
elif not all(files) and not self.allow_none:
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=f"BentoML#{self.__class__.__name__} requires inputs "
f"fields {self.input_names}",
)
else:
task = InferenceTask(
context=InferenceContext(http_headers=req.parsed_headers),
data=files,
)
else:
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=
f"BentoML#{self.__class__.__name__} with multiple inputs "
"accepts requests with Content-Type: multipart/form-data only",
)
return task
def from_http_request(self, req: HTTPRequest) -> MultiFileTask:
if req.headers.content_type != 'multipart/form-data':
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=
f"BentoML#{self.__class__.__name__} only accepts requests "
"with Content-Type: multipart/form-data",
)
else:
_, _, files = HTTPRequest.parse_form_data(req)
files = tuple(files.get(k) for k in self.input_names)
if not any(files):
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=f"BentoML#{self.__class__.__name__} requires inputs "
f"fields {self.input_names}",
)
elif not all(files) and not self.allow_none:
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=f"BentoML#{self.__class__.__name__} requires inputs "
f"fields {self.input_names}",
)
else:
task = InferenceTask(
http_headers=req.headers,
data=files,
)
return task
def from_http_request(self, req: HTTPRequest) -> InferenceTask[BinaryIO]:
if req.parsed_headers.content_type == 'multipart/form-data':
_, _, files = HTTPRequest.parse_form_data(req)
if len(files) != 1:
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=
f"BentoML#{self.__class__.__name__} requires one and at"
" least one file at a time, if you just upgraded from"
" bentoml 0.7, you may need to use MultiFileAdapter instead",
)
else:
input_file = next(iter(files.values()))
task = InferenceTask(
context=InferenceContext(http_headers=req.parsed_headers),
data=input_file,
)
elif req.body:
task = InferenceTask(
context=InferenceContext(http_headers=req.parsed_headers),
data=io.BytesIO(req.body),
)
else:
task = InferenceTask(data=None)
task.discard(
http_status=400,
err_msg=
f'BentoML#{self.__class__.__name__} unexpected HTTP request'
' format',
)
return task
def from_http_request(self, req: HTTPRequest) -> InferenceTask[str]:
if req.headers.content_type == 'multipart/form-data':
_, _, files = HTTPRequest.parse_form_data(req)
if len(files) != 1:
return InferenceTask().discard(
http_status=400,
err_msg=
f"BentoML#{self.__class__.__name__} accepts one text file "
"at a time",
)
input_file = next(iter(files.values()))
bytes_ = input_file.read()
charset = chardet.detect(bytes_)['encoding'] or "utf-8"
else:
bytes_ = req.body
charset = req.headers.charset or "utf-8"
try:
return InferenceTask(
http_headers=req.headers,
data=bytes_.decode(charset),
)
except UnicodeDecodeError:
return InferenceTask().discard(
http_status=400,
err_msg=
f"{self.__class__.__name__}: UnicodeDecodeError for {req.body}",
)
except LookupError:
return InferenceTask().discard(
http_status=400,
err_msg=
f"{self.__class__.__name__}: Unsupported charset {req.charset}",
)
