REST API¶
Each DeepPavlov model can be easily made available for inference as a REST web service. The general method is:
python -m deeppavlov riseapi <config_path> [-d] [-p <port>]
-d: downloads model specific data before starting the service.-p <port>: sets the port to<port>. Overrides default settings fromdeeppavlov/utils/settings/server_config.json.
The command will print the used host and port. Default web service properties
(host, port, POST request arguments) can be modified via changing
deeppavlov/utils/settings/server_config.json file.
API routes¶
/probe¶
Send POST request to <host>:<port>/probe to check if API is working. The
server will send a response ["Test passed"] if it is working. Requests to
/probe are not logged.
/api¶
To get model argument names send GET request to <host>:<port>/api. Server
will return list with argument names.
/docs¶
To interact with the REST API via graphical interface open
<host>:<port>/docs in a browser (Flasgger UI).
Advanced configuration¶
By modifying deeppavlov/utils/settings/server_config.json you can change
host, port, POST request arguments and other properties of the API service.
Properties from common_defaults section are used by default unless
they are overridden by model-specific properties, provided in
model_defaults section of the server_config.json.
Model-specific properties are bound to the model by
server_utils label in metadata/labels section of the model
config. Value of server_utils label from model config should
match with properties key from model_defaults section of
server_config.json.
For example, metadata/labels/server_utils tag from
go_bot/gobot_dstc2.json references to the GoalOrientedBot section
of server_config.json. Therefore, all parameters with non empty (i.e. not
"", not [] etc.) values from model_defaults/GoalOrientedBot will
overwrite the parameter values in common_defaults.
If model_args_names parameter of server_config.json is empty string,
then model argument names are provided as list from chainer/in section of
the model config file, where arguments order corresponds to model API.
When inferencing model via REST api, JSON payload keys should match
model arguments names from chainer/in section.
If model_args_names parameter of server_config.json is list, its values
are used as model argument names instead of the list from model config’s
chainer/in section.
Here are POST request payload examples for some of the library models:
Model |
POST request JSON payload example |
|---|---|
One argument models |
|
NER model |
{“x”:[“Elon Musk launched his cherry Tesla roadster to the Mars orbit”]} |
Intent classification model |
{“x”:[“I would like to go to a restaurant with Asian cuisine this evening”]} |
Automatic spelling correction model |
{“x”:[“errror”]} |
Ranking model |
{“x”:[“What is the average cost of life insurance services?”]} |
Goal-oriented bot |
{“x”:[“Hello, can you help me to find and book a restaurant this evening?”]} |
Multiple arguments models |
|
Question Answering model |
{“context_raw”:[“After 1765, growing philosophical and political differences strained the relationship between Great Britain and its colonies.”],
“question_raw”:[“What strained the relationship between Great Britain and its colonies?”]}
|