Flask based REST API for spaCy, the great and fast NLP framework. Supports the English and German language models and returns the analysis structured by sentences and by token.
Please note that currently the dependency trees and word vectors are not being returned.
- Updated to spaCy 1.8.0
- Default english language
curl http://localhost:5000/api --header 'content-type: application/json' --data '{"text": "This is a text that I want to be analyzed."}' -X POST
You'll receive a JSON in return:
{
'sentences': [[TOKEN, TOKEN, ...], [TOKEN, TOKEN, ...], ...],
'performance': CALCULATION_TIME_IN_SEC,
'version': SPACY_VERSION,
'numOfSentences': NUM_OF_SENTENCES,
'numOfTokens': NUM_OF_TOKENS
}
TOKEN: {
'token': TOKEN,
'lemma': LEMMA,
'tag': TAG,
'ner': NER,
'offsets': {
'begin': BEGIN,
'end': END
},
'oov': OUT_OF_VOCAB,
'stop': IS_STOPWORD,
'url': IS_URL,
'email': IS_MAIL,
'num': IS_NUM,
'pos': POS
}
| Field | Explanation |
|---|---|
| text | One text to be analyzed |
| texts | List of texts to be analyzed |
| fields | Optional. A list of token data fields that should be analyzed. Example: ['pos', 'token'] |
Either 'text' or 'texts' is required.
sudo docker build -t spacy-en .
sudo docker run --name spacy-en -d --net=host spacy-en
curl http://localhost:5000/api --header 'content-type: application/json' --data '{"text": "Angela Merkel loves spending holiday in Italy."}' -X POST
{
"sentences":[
[
{
"offsets":{
"end":6,
"begin":0
},
"token":"Angela",
"stop":false,
"email":false,
"oov":false,
"url":false,
"tag":"NNP",
"pos":"PROPN",
"ner":"PERSON",
"lemma":"angela",
"num":false
},
{
"offsets":{
"end":13,
"begin":7
},
"token":"Merkel",
"stop":false,
"email":false,
"oov":false,
"url":false,
"tag":"NNP",
"pos":"PROPN",
"ner":"PERSON",
"lemma":"merkel",
"num":false
},
{
"offsets":{
"end":19,
"begin":14
},
"token":"loves",
"stop":false,
"email":false,
"oov":false,
"url":false,
"tag":"VBZ",
"pos":"VERB",
"ner":"",
"lemma":"love",
"num":false
},
{
"offsets":{
"end":28,
"begin":20
},
"token":"spending",
"stop":false,
"email":false,
"oov":false,
"url":false,
"tag":"VBG",
"pos":"VERB",
"ner":"",
"lemma":"spend",
"num":false
},
{
"offsets":{
"end":36,
"begin":29
},
"token":"holiday",
"stop":false,
"email":false,
"oov":false,
"url":false,
"tag":"NN",
"pos":"NOUN",
"ner":"",
"lemma":"holiday",
"num":false
},
{
"offsets":{
"end":39,
"begin":37
},
"token":"in",
"stop":true,
"email":false,
"oov":false,
"url":false,
"tag":"IN",
"pos":"ADP",
"ner":"",
"lemma":"in",
"num":false
},
{
"offsets":{
"end":45,
"begin":40
},
"token":"Italy",
"stop":false,
"email":false,
"oov":false,
"url":false,
"tag":"NNP",
"pos":"PROPN",
"ner":"GPE",
"lemma":"italy",
"num":false
},
{
"offsets":{
"end":46,
"begin":45
},
"token":".",
"stop":false,
"email":false,
"oov":false,
"url":false,
"tag":".",
"pos":"PUNCT",
"ner":"",
"lemma":".",
"num":false
}
]
],
"performance":[
0.002523183822631836
],
"numOfTokens":8,
"numOfSentences":1,
"lang":"en",
"error":false,
"version":"1.2.0"
}
curl --request POST \
--url http://localhost:5000/api \
--header 'content-type: application/json' \
--data '{
"texts": ["Here comes Peter.", "And so does Mary."],
"fields": ["pos", "token", "lemma"]
}'
{
"numberOfTexts": 2,
"performance": [
0.003515958786010742
],
"version": "1.2.0",
"texts": [
{
"numOfSentences": 1,
"sentences": [
[
{
"token": "Here",
"pos": "ADV",
"lemma": "here"
},
{
"token": "comes",
"pos": "VERB",
"lemma": "come"
},
{
"token": "Peter",
"pos": "PROPN",
"lemma": "peter"
},
{
"token": ".",
"pos": "PUNCT",
"lemma": "."
}
]
],
"numOfTokens": 4
},
{
"numOfSentences": 1,
"sentences": [
[
{
"token": "And",
"pos": "CONJ",
"lemma": "and"
},
{
"token": "so",
"pos": "ADV",
"lemma": "so"
},
{
"token": "does",
"pos": "VERB",
"lemma": "do"
},
{
"token": "Mary",
"pos": "PROPN",
"lemma": "mary"
},
{
"token": ".",
"pos": "PUNCT",
"lemma": "."
}
]
],
"numOfTokens": 5
}
],
"lang": "en",
"error": false
}