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bbieniek / spacy-api-docker

spaCy REST API, wrapped in a Docker container.

Home Page:https://hub.docker.com/r/bbieniek/spacyapi/

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spaCy API Docker

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

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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: 3.0.0

This set of docker files is based on (https://github.com/jgontrum/spacy-api-docker)

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

Images

Image Description
bbieniek/spacyapi:base_v3 Base image for spaCy 3.0, containing no language model
bbieniek/spacyapi:en_v3 English language model (en_core_web_md), spaCy 3.0
bbieniek/spacyapi:de_v3 German language model (de_core_news_sm), spaCy 3.0
bbieniek/spacyapi:es_v3 Spanish language model (es_core_news_sm), spaCy 3.0
bbieniek/spacyapi:fr_v3 French language model (fr_core_news_sm), spaCy 3.0
bbieniek/spacyapi:pt_v3 Portuguese language model (pt_core_news_sm), spaCy 3.0
bbieniek/spacyapi:it_v3 Italian language model (it_core_news_sm), spaCy 3.0
bbieniek/spacyapi:nl_v3 Dutch language model (nl_core_news_sm), spaCy 3.0
bbieniek/spacyapi:all_v3 Contains EN, DE, ES, PT, NL, IT and FR language models, spaCy 3.0

Usage

docker run -p "127.0.0.1:8080:80" bbieniek/spacyapi:en_v3

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: bbieniek/spacyapi:en_v3
    ports:
      - "127.0.0.1:8080:80"
    restart: always

Running Tests

In order to run unit tests locally pytest is included.

docker run -it bbieniek/spacyapi:en_v3 app/env/bin/pytest app/displacy_service_tests

Special Cases

The API includes rudimentary support for specifying special cases for your deployment. Currently only basic special cases are supported; for example, in the spaCy parlance:

tokenizer.add_special_case("isn't", [{ORTH: "isn't"}])

They can be supplied in an environment variable corresponding to the desired language model. For example, en_special_cases or en_core_web_lg_special_cases. They are configured as a single comma-delimited string, such as "isn't,doesn't,won't".

Use the following syntax to specify basic special case rules, such as for preserving contractions:

docker run -p "127.0.0.1:8080:80" -e en_special_cases="isn't,doesn't" bbieniek/spacyapi:en_v3

You can also configure this in a .env file if using docker-compose as above.

REST API Documentation

GET /ui/

displaCy frontend is available here.

POST /dep

Example request:

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

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_core_web_md'}

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,
    "text": "Pastafarians",
    "type": "NORP"
  },
  {
    "end": 51,
    "start": 42,
    "text": "Coca Cola",
    "type": "ORG"
  }
]

POST /sents

Example request:

{
  "text": "In 2012 I was a mediocre developer. But today I am at least a bit better.",
  "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/sents"
message_text = "In 2012 I was a mediocre developer. But today I am at least a bit better."
headers = {'content-type': 'application/json'}
d = {'text': message_text, 'model': 'en_core_web_md'}

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

Example response:

["In 2012 I was a mediocre developer.", "But today I am at least a bit better."]

POST /sents_dep

Combination of /sents and /dep, returns sentences and dependency parses

Example request:

{
  "text": "In 2012 I was a mediocre developer. But today I am at least a bit better.",
  "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/sents_dep"
message_text = "In 2012 I was a mediocre developer. But today I am at least a bit better."
headers = {'content-type': 'application/json'}
d = {'text': message_text, 'model': 'en_core_web_md'}

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

Example response:

[
  {
    "sentence": "In 2012 I was a mediocre developer.",
    "dep_parse": {
      "arcs": [
        {
          "dir": "left",
          "end": 3,
          "label": "prep",
          "start": 0,
          "text": "In"
        },
        {
          "dir": "right",
          "end": 1,
          "label": "pobj",
          "start": 0,
          "text": "2012"
        },
        {
          "dir": "left",
          "end": 3,
          "label": "nsubj",
          "start": 2,
          "text": "I"
        },
        {
          "dir": "left",
          "end": 6,
          "label": "det",
          "start": 4,
          "text": "a"
        },
        {
          "dir": "left",
          "end": 6,
          "label": "amod",
          "start": 5,
          "text": "mediocre"
        },
        {
          "dir": "right",
          "end": 6,
          "label": "attr",
          "start": 3,
          "text": "developer"
        },
        {
          "dir": "right",
          "end": 7,
          "label": "punct",
          "start": 3,
          "text": "."
        }
      ],
      "words": [
        {
          "tag": "IN",
          "text": "In"
        },
        {
          "tag": "CD",
          "text": "2012"
        },
        {
          "tag": "PRP",
          "text": "I"
        },
        {
          "tag": "VBD",
          "text": "was"
        },
        {
          "tag": "DT",
          "text": "a"
        },
        {
          "tag": "JJ",
          "text": "mediocre"
        },
        {
          "tag": "NN",
          "text": "developer"
        },
        {
          "tag": ".",
          "text": "."
        }
      ]
    }
  },
  {
    "sentence": "But today I am at least a bit better.",
    "dep_parse": {
      "arcs": [
        {
          "dir": "left",
          "end": 11,
          "label": "cc",
          "start": 8,
          "text": "But"
        },
        {
          "dir": "left",
          "end": 11,
          "label": "npadvmod",
          "start": 9,
          "text": "today"
        },
        {
          "dir": "left",
          "end": 11,
          "label": "nsubj",
          "start": 10,
          "text": "I"
        },
        {
          "dir": "left",
          "end": 13,
          "label": "advmod",
          "start": 12,
          "text": "at"
        },
        {
          "dir": "left",
          "end": 15,
          "label": "advmod",
          "start": 13,
          "text": "least"
        },
        {
          "dir": "left",
          "end": 15,
          "label": "det",
          "start": 14,
          "text": "a"
        },
        {
          "dir": "left",
          "end": 16,
          "label": "npadvmod",
          "start": 15,
          "text": "bit"
        },
        {
          "dir": "right",
          "end": 16,
          "label": "acomp",
          "start": 11,
          "text": "better"
        },
        {
          "dir": "right",
          "end": 17,
          "label": "punct",
          "start": 11,
          "text": "."
        }
      ],
      "words": [
        {
          "tag": "CC",
          "text": "But"
        },
        {
          "tag": "NN",
          "text": "today"
        },
        {
          "tag": "PRP",
          "text": "I"
        },
        {
          "tag": "VBP",
          "text": "am"
        },
        {
          "tag": "IN",
          "text": "at"
        },
        {
          "tag": "JJS",
          "text": "least"
        },
        {
          "tag": "DT",
          "text": "a"
        },
        {
          "tag": "NN",
          "text": "bit"
        },
        {
          "tag": "RBR",
          "text": "better"
        },
        {
          "tag": ".",
          "text": "."
        }
      ]
    }
  }
]

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": "2.2.4"
}

About

spaCy REST API, wrapped in a Docker container.

https://hub.docker.com/r/bbieniek/spacyapi/

License:MIT License

Languages

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