Ready-to-use Docker images for the spaCy NLP library.
Try the demo for spaCy 1.9.0 or spaCy 2.0.0 (alpha)!
- Use the awesome spaCy NLP framwork 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 and French.
- Automated builds to stay up to date with spaCy.
- Used spaCy version: 1.9.0 / 2.0.0alpha.
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.
| Image | Description | Build |
|---|---|---|
| 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:base_v2 | Base image for spaCy 2.0 |  |
| jgontrum/spacyapi:en_v2 | English language model for spaCy 2.0 | |
| jgontrum/spacyapi:de_v2 | German language model for spaCy 2.0 | |
| jgontrum/spacyapi:es_v2 | Spanish language model for spaCy 2.0 | |
| jgontrum/spacyapi:all_v2 | Contains EN, DE and FR language models for spaCy 2.0 | |
| jgontrum/spacyapi:en-legacy | Old API with English model | legacy |
| jgontrum/spacyapi:de-legacy | Old API with German model | legacy |
docker run -p "127.0.0.1:8080:80" jgontrum/spacyapi:en
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.
version: '2'
services:
spacyapi:
image: jgontrum/spacyapi:en
ports:
- "127.0.0.1:8080:80"
restart: always
displaCy frontend is available here.
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:https://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."
}
]
}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:https://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"
}
]List the names of models installed on the server.
Example request:
GET /models
Example response:
["en", "de"]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"]
}Show the used spaCy version.
Example request:
GET /version
Example response:
{
"spacy": "1.9.0"
}