spaCy REST API, wrapped in a Docker container.
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chore(readme): correct spacy version is 2.0.11
Latest commit ba693a3 Jun 30, 2018

README.md

spaCy API Docker

ENGLISH DEMO | GERMAN DEMO

Ready-to-use Docker images for the spaCy NLP library.

Features

  • Use the awesome spaCy NLP framework with other programming languages.
  • Better scaling: One NLP - multiple services.
  • Build using the official spaCy REST services.
  • Dependency parsing visualisation with displaCy.
  • Docker images for English, German, Spanish, Italian, Dutch and French.
  • Automated builds to stay up to date with spaCy.
  • Current spaCy version: 2.0.11

Please note that this is a completely new API and is incompatible with the previous one. If you still need them, use jgontrum/spacyapi:en-legacy or jgontrum/spacyapi:de-legacy.

Documentation, API- and frontend code based upon spaCy REST services by Explosion AI.


Images

Image Description
jgontrum/spacyapi:base_v2 Base image for spaCy 2.0, containing no language model
jgontrum/spacyapi:en_v2 English language model, spaCy 2.0
jgontrum/spacyapi:de_v2 German language model, spaCy 2.0
jgontrum/spacyapi:es_v2 Spanish language model, spaCy 2.0
jgontrum/spacyapi:fr_v2 French language model, spaCy 2.0
jgontrum/spacyapi:pt_v2 Portuguese language model, spaCy 2.0
jgontrum/spacyapi:it_v2 Italian language model, spaCy 2.0
jgontrum/spacyapi:nl_v2 Dutch language model, spaCy 2.0
jgontrum/spacyapi:all_v2 Contains EN, DE, ES, PT, NL, IT and FR language models, spaCy 2.0
OLD RELEASES
jgontrum/spacyapi:base Base image, containing no language model
jgontrum/spacyapi:latest English language model
jgontrum/spacyapi:en English language model
jgontrum/spacyapi:de German language model
jgontrum/spacyapi:es Spanish language model
jgontrum/spacyapi:fr French language model
jgontrum/spacyapi:all Contains EN, DE, ES and FR language models
jgontrum/spacyapi:en-legacy Old API with English model
jgontrum/spacyapi:de-legacy Old API with German model

Usage

docker run -p "127.0.0.1:8080:80" jgontrum/spacyapi:en_v2

All models are loaded at start up time. Depending on the model size and server performance, this can take a few minutes.

The displaCy frontend is available at /ui.

Docker Compose

version: '2'

services:
  spacyapi:
    image: jgontrum/spacyapi:en_v2
    ports:
      - "127.0.0.1:8080:80"
    restart: always

REST API Documentation

GET /ui/

displaCy frontend is available here.


POST /dep/

Example request:

{
    "text": "They ate the pizza with anchovies",
    "model":"en",
    "collapse_punctuation": 0,
    "collapse_phrases": 1
}
Name Type Description
text string text to be parsed
model string identifier string for a model installed on the server
collapse_punctuation boolean Merge punctuation onto the preceding token?
collapse_phrases boolean Merge noun chunks and named entities into single tokens?

Example request using the Python Requests library:

import json
import requests

url = "http://localhost:8000/dep"
message_text = "They ate the pizza with anchovies"
headers = {'content-type': 'application/json'}
d = {'text': message_text, 'model': 'en'}

response = requests.post(url, data=json.dumps(d), headers=headers)
r = response.json()

Example response:

{
    "arcs": [
        { "dir": "left", "start": 0, "end": 1, "label": "nsubj" },
        { "dir": "right", "start": 1, "end": 2, "label": "dobj" },
        { "dir": "right", "start": 1, "end": 3, "label": "prep" },
        { "dir": "right", "start": 3, "end": 4, "label": "pobj" },
        { "dir": "left", "start": 2, "end": 3, "label": "prep" }
    ],
    "words": [
        { "tag": "PRP", "text": "They" },
        { "tag": "VBD", "text": "ate" },
        { "tag": "NN", "text": "the pizza" },
        { "tag": "IN", "text": "with" },
        { "tag": "NNS", "text": "anchovies" }
    ]
}
Name Type Description
arcs array data to generate the arrows
dir string direction of arrow ("left" or "right")
start integer offset of word the arrow starts on
end integer offset of word the arrow ends on
label string dependency label
words array data to generate the words
tag string part-of-speech tag
text string token

Curl command:

curl -s localhost:8000/dep -d '{"text":"Pastafarians are smarter than people with Coca Cola bottles.", "model":"en"}'
{
  "arcs": [
    {
      "dir": "left",
      "end": 1,
      "label": "nsubj",
      "start": 0
    },
    {
      "dir": "right",
      "end": 2,
      "label": "acomp",
      "start": 1
    },
    {
      "dir": "right",
      "end": 3,
      "label": "prep",
      "start": 2
    },
    {
      "dir": "right",
      "end": 4,
      "label": "pobj",
      "start": 3
    },
    {
      "dir": "right",
      "end": 5,
      "label": "prep",
      "start": 4
    },
    {
      "dir": "right",
      "end": 6,
      "label": "pobj",
      "start": 5
    }
  ],
  "words": [
    {
      "tag": "NNPS",
      "text": "Pastafarians"
    },
    {
      "tag": "VBP",
      "text": "are"
    },
    {
      "tag": "JJR",
      "text": "smarter"
    },
    {
      "tag": "IN",
      "text": "than"
    },
    {
      "tag": "NNS",
      "text": "people"
    },
    {
      "tag": "IN",
      "text": "with"
    },
    {
      "tag": "NNS",
      "text": "Coca Cola bottles."
    }
  ]
}

POST /ent/

Example request:

{
    "text": "When Sebastian Thrun started working on self-driving cars at Google in 2007, few people outside of the company took him seriously.",
    "model": "en"
}
Name Type Description
text string text to be parsed
model string identifier string for a model installed on the server

Example request using the Python Requests library:

import json
import requests

url = "http://localhost:8000/ent"
message_text = "When Sebastian Thrun started working on self-driving cars at Google in 2007, few people outside of the company took him seriously."
headers = {'content-type': 'application/json'}
d = {'text': message_text, 'model': 'en'}

response = requests.post(url, data=json.dumps(d), headers=headers)
r = response.json()

Example response:

[
    { "end": 20, "start": 5,  "type": "PERSON" },
    { "end": 67, "start": 61, "type": "ORG" },
    { "end": 75, "start": 71, "type": "DATE" }
]
Name Type Description
end integer character offset the entity ends after
start integer character offset the entity starts on
type string entity type
curl -s localhost:8000/ent -d '{"text":"Pastafarians are smarter than people with Coca Cola bottles.", "model":"en"}'
[
  {
    "end": 12,
    "start": 0,
    "type": "NORP"
  },
  {
    "end": 51,
    "start": 42,
    "type": "ORG"
  }
]

GET /models

List the names of models installed on the server.

Example request:

GET /models

Example response:

["en", "de"]

GET /{model}/schema/

Example request:

GET /en/schema
Name Type Description
model string identifier string for a model installed on the server

Example response:

{
  "dep_types": ["ROOT", "nsubj"],
  "ent_types": ["PERSON", "LOC", "ORG"],
  "pos_types": ["NN", "VBZ", "SP"]
}

GET /version

Show the used spaCy version.

Example request:

GET /version

Example response:

{
  "spacy": "1.9.0"
}