Serialization & Deserialization for Requests
Serialization & Deserialization for Requests
BOINC AI Inference Endpount comes with a default serving container which is used for all supported Transformers and Sentence-Transformers tasks and for custom inference handler. The serving container takes care of serialization and deserialization of the request and response payloads based on the content-type
and accept
headers of the request. That means that when you send a request with a JSON body and a content-type: application/json
header, the serving container will deserialize the JSON payload into a Python dictionary and pass it to the inference handler and if you send a request with a accept: image/png
header, the serving container will seralize the response from the task/custom handler into a image.
Below is a list of supported content-types
and the deserialized payload that is passed to the inference handler.
application/json
dict
text/csv
raw
text/plain
raw
image/png
binary
image/jpeg
binary
image/jpg
binary
image/tiff
binary
image/bmp
binary
image/gif
binary
image/webp
binary
image/x-image
binary
audio/x-flac
{"inputs": bytes(body)}
audio/flac
{"inputs": bytes(body)}
audio/mpeg
{"inputs": bytes(body)}
audio/x-mpeg-3
{"inputs": bytes(body)}
audio/wave
{"inputs": bytes(body)}
audio/wav
{"inputs": bytes(body)}
audio/x-wav
{"inputs": bytes(body)}
audio/ogg
{"inputs": bytes(body)}
audio/x-audio
{"inputs": bytes(body)}
audio/webm
{"inputs": bytes(body)}
audio/webm;codecs=opus
{"inputs": bytes(body)}
audio/AMR
{"inputs": bytes(body)}
audio/amr
{"inputs": bytes(body)}
audio/AMR-WB
{"inputs": bytes(body)}
audio/AMR-WB+
{"inputs": bytes(body)}
audio/m4a
{"inputs": bytes(body)}
audio/x-m4a
{"inputs": bytes(body)}
Below is a list of supported accept
headers and the serialized payload is returned.
application/json
JSON
text/csv
raw
text/plain
raw
image/png
binary
image/jpeg
binary
image/jpg
binary
image/tiff
binary
image/bmp
binary
image/gif
binary
image/webp
binary
image/x-image
binary
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