Fix #21 (#22)

* Conditionally enable sense2vec for performance improvements

* Disable sense2vec in unrelated pipeline uses

* Test HTTP exceptions

* Update Docker image tagging convention

* Conditionally disable sense2vec

README.md

@@ -2,7 +2,7 @@
 
 [![Built with spaCy](https://img.shields.io/badge/built%20with-spaCy-09a3d5.svg)](https://spacy.io)
 
-This project provides industrial-strength NLP for multiple languages via [spaCy](https://spacy.io/) and [sense2vec](https://github.com/explosion/sense2vec) over a containerized HTTP API.
+This project provides industrial-strength NLP via [spaCy](https://spacy.io/) and [sense2vec](https://github.com/explosion/sense2vec) over a containerized HTTP API.
 
 ## Installation
 
@@ -10,18 +10,11 @@ This project provides industrial-strength NLP for multiple languages via [spaCy]
 
 Install [Docker](https://hub.docker.com/search/?type=edition&offering=community).
 
-You can find specific tags (say for example, a French model) on the [Docker Hub repository](https://hub.docker.com/repository/docker/neelkamath/spacy-server/tags?page=1).
-
-For example, to run an English model at `http://localhost:8000`, run:
-```
-docker run --rm -e SPACY_MODEL=en_core_web_sm -p 8000:8000 neelkamath/spacy-server:v1-en_core_web_sm
-```
-
 ### Generating an SDK
 
 You can generate a wrapper for the HTTP API using [OpenAPI Generator](https://openapi-generator.tech/) on the file [`https://raw.githubusercontent.com/neelkamath/spacy-server/master/docs/openapi.yaml`](https://raw.githubusercontent.com/neelkamath/spacy-server/master/docs/openapi.yaml).
 
-## [Usage](https://neelkamath.gitlab.io/spacy-server/)
+## [Usage](https://hub.docker.com/r/neelkamath/spacy-server)
 
 ## [Contributing](docs/CONTRIBUTING.md)
 

docker/Dockerfile

-FROM python:3.8
+FROM python:3.8 AS base
 WORKDIR /app
-ENV PYTHONUNBUFFERED 1
+ARG SPACY_MODEL
+ENV PYTHONUNBUFFERED=1 SENSE2VEC=0 SPACY_MODEL=$SPACY_MODEL
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
-ARG SPACY_MODEL
 RUN python -m spacy download $SPACY_MODEL
 COPY src/main.py .
-COPY src/s2v_old/ s2v_old/
 EXPOSE 8000
 HEALTHCHECK --timeout=2s --start-period=2s --retries=1 \
     CMD curl -f http://localhost:8000/health_check
 RUN useradd user
 USER user
-CMD ["uvicorn", "main:app", "--host", "0.0.0.0"]
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0"]
\ No newline at end of file
+
+FROM base
+ENV SENSE2VEC 1
+COPY src/s2v_old/ src/s2v_old/
\ No newline at end of file

docker/docker-compose.override.yml

 version: '3.7'
 services:
   app:
-    command: sh scripts/setup.sh 'uvicorn src.main:app --host 0.0.0.0 --reload'
-    ports: ['8000:8000']
+    command: sh -c '. scripts/setup.sh && uvicorn src.main:app --host 0.0.0.0 --reload'
+    ports: ['8000:8000']
\ No newline at end of file
+    environment:
+      SPACY_MODEL:
+      SENSE2VEC:
\ No newline at end of file

docker/docker-compose.test.yml

 version: '3.7'
 services:
   app:
-    command: sh scripts/setup.sh pytest
+    command: sh -c '. scripts/setup.sh && pytest'
     environment:
+      SENSE2VEC: 1
 
       # Since any model will do, tests have been written only for the en_core_web_sm model because of its combination of
       # speed, features, and accuracy.

docker/docker-compose.yml

-# It is not possible to use a Docker volume to cache the dependencies because subsequent usage of the volume
-# occasionally gets corrupted for an unknown reason. Hence, a virtual environment is to be used instead. It is known
-# that virtual environments aren't needed in Docker because isolation is already provided; we use it as a cache instead.
+# A virtual environment caches dependencies instead of a Docker volume because the volume randomly gets corrupted.
 
 version: '3.7'
 services:
   app:
     image: python:3.8
     working_dir: /app
-    environment:
-      SPACY_MODEL:
     volumes:
       - type: bind
         source: .

docs/CONTRIBUTING.md

@@ -9,6 +9,6 @@ If you're forking the repo to develop the project as your own and not just to se
 1. Clone the repository using one of the following methods.
     - SSH: `git clone git@github.com:neelkamath/spacy-server.git`
     - HTTPS: `git clone https://github.com/neelkamath/spacy-server.git`
-1. Download the [pretrained vectors](https://github.com/explosion/sense2vec/releases/download/v1.0.0/s2v_reddit_2015_md.tar.gz). Extract it into the project's `src` directory.
+1. If you are not going to use sense2vec, skip this step. Download the [pretrained vectors](https://github.com/explosion/sense2vec/releases/download/v1.0.0/s2v_reddit_2015_md.tar.gz). Extract it into the project's `src` directory.
 
 ## [Developing](developing.md)
\ No newline at end of file

docs/developing.md

@@ -2,12 +2,12 @@
 
 ## Server
 
-Replace `<MODEL>` with the name of the [spaCy model](https://spacy.io/models) (e.g., `en_core_web_sm`, `fr_core_news_md`). The model must be compatible with the spaCy version specified in [requirements.txt](../requirements.txt).
+Replace `<MODEL>` with the name of the [spaCy model](https://spacy.io/models) (e.g., `en_core_web_sm`, `fr_core_news_md`). The model must be compatible with the spaCy version specified in [requirements.txt](../requirements.txt). Replace `<ENABLED>` with `1` or `0` to enable to disable sense2vec respectively.
 
 ### Development
 
 ```
-SPACY_MODEL=<MODEL> docker-compose -p dev --project-directory . \
+SPACY_MODEL=<MODEL> SENSE2VEC=<ENABLED> docker-compose -p dev --project-directory . \
     -f docker/docker-compose.yml -f docker/docker-compose.override.yml up --build
 ```
 
@@ -15,19 +15,29 @@ The server will be running on `http://localhost:8000`, and has automatic reload
 
 ### Testing
 
-```
-docker-compose -p test --project-directory . -f docker/docker-compose.yml -f docker/docker-compose.test.yml \
-    up --build --abort-on-container-exit --exit-code-from app
-```
+- For noninteractive environments (e.g., CI pipelines), you can run all the tests with the single command:
+    ```
+    docker-compose -p test --project-directory . -f docker/docker-compose.yml -f docker/docker-compose.test.yml \
+        up --build --abort-on-container-exit --exit-code-from app
+    ```
+- For faster iterations (e.g., while developing), you can run the tests interactively. Changes to the source code will automatically be mirrored in the container.
+    1. Run:
+        ```
+        docker-compose -p test --project-directory . -f docker/docker-compose.yml -f docker/docker-compose.test.yml \
+            run --service-ports app bash
+       ```
+    1. `. scripts/setup.sh` (run this command every time you update `requirements.txt`)
+    1. Execute tests any number of times you want with pytest (e.g., `pytest`).
+    1. After you're done testing, exit the container by running `exit`.
 
 ### Production
 
 ```
-docker build --build-arg SPACY_MODEL=<MODEL> -t spacy-server -f docker/Dockerfile .
-docker run --rm -e SPACY_MODEL=<MODEL> -p 8000:8000 spacy-server
+docker build <TARGET> --build-arg SPACY_MODEL=<MODEL> -t spacy-server -f docker/base.Dockerfile .
 ```
+Replace `<TARGET>` with `--target base` if you want to disable sense2vec, and an empty string otherwise.
 
-The container `EXPOSE`s port `8000`.
+The container `EXPOSE`s port `8000`. Run using `docker run --rm -p 8000:8000 spacy-server`.
 
 ## Specification
 
@@ -61,7 +71,10 @@ Open `redoc-static.html` in your browser.
 
 ## Releases
 
-- Create a GitHub release (this will automatically create the git tag). If you bumped the version in `docs/openapi.yaml`, then create a new release. If you haven't bumped the version but have updated the HTTP API's functionality, delete the existing GitHub release and git tag, and create a new one. Otherwise, skip this step. The release's title should be the features included (e.g., `NER, POS tagging, sentencizer, tokenizer, and sense2vec`). The tag should be the HTTP API's version (e.g., `v1`). The release's body should be ```Download and open the release asset, `redoc-static.html`, in your browser to view the HTTP API documentation.```. Upload the asset named `redoc-static.html` which contains the HTTP API docs.
+- If you haven't updated the HTTP API functionality, skip this step.
+    1. If you haven't bumped the version in the OpenAPI spec, delete the corresponding GitHub release and git tag.
+    1. Generate  `redoc-static.html`: `npx redoc-cli bundle docs/openapi.yaml -o redoc-static.html --title 'spaCy Server'`
+    1. Create a GitHub release. The release's body should be ```Download and open the release asset, `redoc-static.html`, in your browser to view the HTTP API documentation.```. Upload `redoc-static.html` as an asset.
 - If required, update the [Docker Hub repository](https://hub.docker.com/r/neelkamath/spacy-server)'s **Overview**.
 - For every commit to the `master` branch in which the tests have passed, the following will automatically be done.
     - The new images will be uploaded to Docker Hub.

docs/openapi.yaml

 openapi: 3.0.2
 info:
   title: spaCy Server
-  version: '1'
+  version: '2'
   description: |
     Industrial-strength NLP via [spaCy](https://spacy.io) and [sense2vec](https://github.com/explosion/sense2vec). No
     knowledge of spaCy or sense2vec is required to use this service.
@@ -26,8 +26,8 @@ paths:
   /ner:
     post:
       tags: [nlp]
-      description: Named entity recognition. Similar phrases will also be provided via sense2vec. The pretrained model
-        must have the `ner` and `parser` pipeline components to use this endpoint.
+      description: Named entity recognition. The pretrained model must have the `ner` and `parser` pipeline components
+        to use this endpoint. If a sense2vec model was bundled with the service, similar phrases can also be provided.
       operationId: ner
       requestBody:
         required: true
@@ -39,7 +39,7 @@ paths:
                 - Net income was $9.4 million compared to the prior year of $2.7 million. Google is a big company.
                 - Revenue exceeded twelve billion dollars, with a loss of $1b.
             schema:
-              $ref: '#/components/schemas/Sections'
+              $ref: '#/components/schemas/NERRequest'
       responses:
         '200':
           description: Labeled text, with phrases similar to each entity
@@ -74,13 +74,21 @@ paths:
                         text_with_ws: Sundar Pichai
                     text: Google is headed by Sundar Pichai.
               schema:
-                $ref: '#/components/schemas/NamedEntities'
+                $ref: '#/components/schemas/NERResponse'
         '400':
           description: The pretrained model lacks the `ner` or `parser` pipeline components.
           content:
             application/json:
-              example:
-                detail: The pretrained model (en_trf_bertbaseuncased_lg) doesn't support named entity recognition.
+              examples:
+                invalid_model:
+                  summary: The spaCy model lacks the required pipeline components.
+                  value:
+                    detail: The pretrained model (en_trf_bertbaseuncased_lg) doesn't support named entity recognition.
+                sense2vec_disabled:
+                  summary: Similar phrases via sense2vec were requested, but a sense2vec model wasn't bundled with the
+                    service.
+                  value:
+                    detail: There is no sense2vec model bundled with this service.
               schema:
                 $ref: '#/components/schemas/InvalidModel'
   /pos:
@@ -225,18 +233,22 @@ paths:
           description: All systems are operational
 components:
   schemas:
-    Sections:
+    NERRequest:
       type: object
       properties:
         sections:
           description:
-            Although you could pass the full text as a single array item, it would be faster to split large text
-            into multiple items. Each item needn't be semantically related.
+            Although you could pass the full text as a single array item, it would be faster to split large text into
+            multiple items. Each item needn't be semantically related.
           type: array
           items:
             type: string
+        sense2vec:
+          description: Whether to also compute similar phrases using sense2vec (significantly slower)
+          type: boolean
+          default: false
       required: [sections]
-    NamedEntities:
+    NERResponse:
       type: object
       properties:
         data:
@@ -268,7 +280,7 @@ components:
                       description: The entity’s lemma.
                     sense2vec:
                       type: array
-                      description: Phrases similar to the entity
+                      description: Phrases similar to the entity (empty if sense2vec was disabled)
                       items:
                         type: object
                         properties:

requirements.txt

@@ -2,6 +2,7 @@
 # particular versions.
 spacy==2.2.3
 sense2vec==1.0.2
+
 fastapi==0.45.0
 uvicorn==0.10.8
 pytest>=4.6.7,<5
\ No newline at end of file

scripts/deploy.sh

 #!/usr/bin/env sh
 
-# Builds and uploads every image (e.g., neelkamath/spacy-server:v1-en_core_web_sm) to Docker Hub.
+# Builds and uploads every image (e.g., neelkamath/spacy-server:2-en_core_web_sm-sense2vec) to Docker Hub.
 
 # Get the HTTP API version.
 version=$(grep version docs/openapi.yaml -m 1)
 version=${version#*: }
-version=v$(echo "$version" | cut -d "'" -f 2)
+version=$(echo "$version" | cut -d "'" -f 2)
 
 # Log in.
 echo "$DOCKER_HUB_PASSWORD" | docker login -u "$DOCKER_HUB_USER" --password-stdin https://index.docker.io/v1/
 
 # Build and upload the images.
-while IFS='' read -r model || [ -n "$model" ]; do
-  tag="$DOCKER_HUB_USER"/spacy-server:"$version"-"$model"
-  docker build --build-arg SPACY_MODEL="$model" -t "$tag" -f docker/Dockerfile .
-  docker push "$tag"
-  docker rmi "$tag" # Delete the image to prevent the device (e.g., CI runner) from running out of space and crashing.
+while IFS='' read -r spacy_model || [ -n "$spacy_model" ]; do
+  base_tag="$DOCKER_HUB_USER"/spacy-server:"$version"-"$spacy_model"
+  sense2vec_tag="$base_tag"-sense2vec
+  docker build --target base --build-arg SPACY_MODEL="$spacy_model" -t "$base_tag" -f docker/Dockerfile .
+  docker build --build-arg SPACY_MODEL="$spacy_model" -t "$sense2vec_tag" -f docker/Dockerfile .
+  docker push "$base_tag"
+  docker push "$sense2vec_tag"
+  docker rmi "$base_tag" "$sense2vec_tag" # Prevent the device (e.g., CI runner) from running out of space and crashing.
 done <scripts/models.txt

scripts/setup.sh

 #!/usr/bin/env sh
 
-# Executes a command in a virtual environment (e.g., <sh setup.sh 'uvicorn main:app --reload'>).
+# Sets up the development environment.
 
 python -m venv venv
 . venv/bin/activate
 pip install -r requirements.txt
 python -m spacy download "$SPACY_MODEL"
-$1

src/main.py

@@ -11,34 +11,46 @@ import starlette.status
 
 app = fastapi.FastAPI()
 model = os.getenv('SPACY_MODEL')
-pipeline_error = 'The pretrained model ({})'.format(model) + " doesn't support {}."
+pipeline_error = 'The pretrained model ({})'.format(model) \
+                 + " doesn't support {}."
 nlp = spacy.load(model)
-nlp.add_pipe(sense2vec.Sense2VecComponent(nlp.vocab).from_disk('src/s2v_old'))
+if os.getenv('SENSE2VEC') == '1':
+    nlp.add_pipe(
+        sense2vec.Sense2VecComponent(nlp.vocab).from_disk('src/s2v_old')
+    )
 
 
-class SectionsModel(pydantic.BaseModel):
+class NERRequest(pydantic.BaseModel):
     sections: typing.List[str]
+    sense2vec: bool = False
 
 
 @app.post('/ner')
-async def recognize_named_entities(request: SectionsModel):
+async def recognize_named_entities(request: NERRequest):
     if not nlp.has_pipe('ner') or not nlp.has_pipe('parser'):
         raise fastapi.HTTPException(
             status_code=400,
             detail=pipeline_error.format('named entity recognition')
         )
+    if request.sense2vec and not nlp.has_pipe('sense2vec'):
+        raise fastapi.HTTPException(
+            status_code=400,
+            detail='There is no sense2vec model bundled with this service.'
+        )
     response = {'data': []}
     for doc in nlp.pipe(request.sections, disable=['tagger']):
         for sent in doc.sents:
-            entities = [build_entity(ent) for ent in sent.ents]
+            entities = [
+                build_entity(ent, request.sense2vec) for ent in sent.ents
+            ]
             data = {'text': sent.text, 'entities': entities}
             response['data'].append(data)
     return response
 
 
-def build_entity(ent):
+def build_entity(ent, use_sense2vec):
     similar = []
-    if ent._.in_s2v:
+    if use_sense2vec and ent._.in_s2v:
         for data in ent._.s2v_most_similar():
             similar.append(
                 {'phrase': data[0][0], 'similarity': float(data[1])}
@@ -69,7 +81,8 @@ async def tag_parts_of_speech(request: TextModel):
             detail=pipeline_error.format('part-of-speech tagging')
         )
     data = []
-    for token in [build_token(token) for token in nlp(request.text)]:
+    doc = nlp(request.text, disable=['sense2vec'])
+    for token in [build_token(token) for token in doc]:
         text = token['sent']
         del token['sent']
         if text in [obj['text'] for obj in data]:
@@ -126,7 +139,7 @@ def build_token(token):
 
 @app.post('/tokenizer')
 async def tokenize(request: TextModel):
-    doc = nlp(request.text, disable=['tagger', 'parser', 'ner'])
+    doc = nlp(request.text, disable=['tagger', 'parser', 'ner', 'sense2vec'])
     return {'tokens': [token.text for token in doc]}
 
 
@@ -137,7 +150,7 @@ async def sentencize(request: TextModel):
             status_code=400,
             detail=pipeline_error.format('sentence segmentation')
         )
-    doc = nlp(request.text, disable=['tagger', 'ner'])
+    doc = nlp(request.text, disable=['tagger', 'ner', 'sense2vec'])
     return {'sentences': [sent.text for sent in doc.sents]}
 
 

src/outputs/ner/sense2vec_disabled.json

+{
+  "data": [
+    {
+      "text": "Net income was $9.4 million compared to the prior year of $2.7 million.",
+      "entities": [
+        {
+          "text": "$9.4 million",
+          "label": "MONEY",
+          "start_char": 15,
+          "end_char": 27,
+          "lemma": "$ 9.4 million",
+          "start": 3,
+          "end": 6,
+          "text_with_ws": "$9.4 million ",
+          "sense2vec": []
+        },
+        {
+          "text": "the prior year",
+          "label": "DATE",
+          "start_char": 40,
+          "end_char": 54,
+          "lemma": "the prior year",
+          "start": 8,
+          "end": 11,
+          "text_with_ws": "the prior year ",
+          "sense2vec": []
+        },
+        {
+          "text": "$2.7 million",
+          "label": "MONEY",
+          "start_char": 58,
+          "end_char": 70,
+          "lemma": "$ 2.7 million",
+          "start": 12,
+          "end": 15,
+          "text_with_ws": "$2.7 million",
+          "sense2vec": []
+        }
+      ]
+    },
+    {
+      "text": "Google is a big company.",
+      "entities": [
+        {
+          "text": "Google",
+          "label": "ORG",
+          "start_char": 72,
+          "end_char": 78,
+          "lemma": "Google",
+          "start": 16,
+          "end": 17,
+          "text_with_ws": "Google ",
+          "sense2vec": []
+        }
+      ]
+    },
+    {
+      "text": "Revenue exceeded twelve billion dollars, with a loss of $1b.",
+      "entities": [
+        {
+          "text": "twelve billion dollars",
+          "label": "MONEY",
+          "start_char": 17,
+          "end_char": 39,
+          "lemma": "twelve billion dollar",
+          "start": 2,
+          "end": 5,
+          "text_with_ws": "twelve billion dollars",
+          "sense2vec": []
+        },
+        {
+          "text": "1b",
+          "label": "MONEY",
+          "start_char": 57,
+          "end_char": 59,
+          "lemma": "1b",
+          "start": 11,
+          "end": 12,
+          "text_with_ws": "1b",
+          "sense2vec": []
+        }
+      ]
+    }
+  ]
+}
\ No newline at end of file

src/outputs/ner.json → src/outputs/ner/sense2vec_enabled.json

 {
   "data": [
     {
+      "text": "Net income was $9.4 million compared to the prior year of $2.7 million.",
       "entities": [
         {
-          "end": 6,
-          "end_char": 27,
+          "text": "$9.4 million",
           "label": "MONEY",
+          "start_char": 15,
+          "end_char": 27,
           "lemma": "$ 9.4 million",
-          "sense2vec": [],
           "start": 3,
-          "start_char": 15,
-          "text": "$9.4 million",
-          "text_with_ws": "$9.4 million "
+          "end": 6,
+          "text_with_ws": "$9.4 million ",
+          "sense2vec": []
         },
         {
-          "end": 11,
-          "end_char": 54,
+          "text": "the prior year",
           "label": "DATE",
+          "start_char": 40,
+          "end_char": 54,
           "lemma": "the prior year",
+          "start": 8,
+          "end": 11,
+          "text_with_ws": "the prior year ",
           "sense2vec": [
             {
               "phrase": "the previous year",
@@ -59,17 +64,17 @@
               "phrase": "the entire year",
               "similarity": 0.6915000081062317
             }
-          ],
-          "start": 8,
-          "start_char": 40,
-          "text": "the prior year",
-          "text_with_ws": "the prior year "
+          ]
         },
         {
-          "end": 15,
-          "end_char": 70,
+          "text": "$2.7 million",
           "label": "MONEY",
+          "start_char": 58,
+          "end_char": 70,
           "lemma": "$ 2.7 million",
+          "start": 12,
+          "end": 15,
+          "text_with_ws": "$2.7 million",
           "sense2vec": [
             {
               "phrase": "$1 million",
@@ -111,22 +116,22 @@
               "phrase": "$2 million",
               "similarity": 0.7371000051498413
             }
-          ],
-          "start": 12,
-          "start_char": 58,
-          "text": "$2.7 million",
-          "text_with_ws": "$2.7 million"
+          ]
         }
-      ],
-      "text": "Net income was $9.4 million compared to the prior year of $2.7 million."
+      ]
     },
     {
+      "text": "Google is a big company.",
       "entities": [
         {
-          "end": 17,
-          "end_char": 78,
+          "text": "Google",
           "label": "ORG",
+          "start_char": 72,
+          "end_char": 78,
           "lemma": "Google",
+          "start": 16,
+          "end": 17,
+          "text_with_ws": "Google ",
           "sense2vec": [
             {
               "phrase": " Google",
@@ -168,33 +173,33 @@
               "phrase": "Yahoo",
               "similarity": 0.8037999868392944
             }
-          ],
-          "start": 16,
-          "start_char": 72,
-          "text": "Google",
-          "text_with_ws": "Google "
+          ]
         }
-      ],
-      "text": "Google is a big company."
+      ]
     },
     {
+      "text": "Revenue exceeded twelve billion dollars, with a loss of $1b.",
       "entities": [
         {
-          "end": 5,
-          "end_char": 39,
+          "text": "twelve billion dollars",
           "label": "MONEY",
+          "start_char": 17,
+          "end_char": 39,
           "lemma": "twelve billion dollar",
-          "sense2vec": [],
           "start": 2,
-          "start_char": 17,
-          "text": "twelve billion dollars",
-          "text_with_ws": "twelve billion dollars"
+          "end": 5,
+          "text_with_ws": "twelve billion dollars",
+          "sense2vec": []
         },
         {
-          "end": 12,
-          "end_char": 59,
+          "text": "1b",
           "label": "MONEY",
+          "start_char": 57,
+          "end_char": 59,
           "lemma": "1b",
+          "start": 11,
+          "end": 12,
+          "text_with_ws": "1b",
           "sense2vec": [
             {
               "phrase": "100m",
@@ -236,14 +241,9 @@
               "phrase": "100B",
               "similarity": 0.8209999799728394
             }
-          ],
-          "start": 11,
-          "start_char": 57,
-          "text": "1b",
-          "text_with_ws": "1b"
+          ]
         }
-      ],
-      "text": "Revenue exceeded twelve billion dollars, with a loss of $1b."
+      ]
     }
   ]
 }
\ No newline at end of file

src/test_main.py

@@ -5,29 +5,51 @@ import starlette.testclient
 
 client = starlette.testclient.TestClient(main.app)
 
+ner_body = {
+    'sections': [
+        'Net income was $9.4 million compared to the prior year of $2.7 '
+        + 'million. Google is a big company.',
+        'Revenue exceeded twelve billion dollars, with a loss of $1b.'
+    ]
+}
+ner_sense2vec_body = {**ner_body, 'sense2vec': True}
 
-def test_ner():
-    body = {
-        'sections': [
-            'Net income was $9.4 million compared to the prior year of $2.7 '
-            + 'million. Google is a big company.',
-            'Revenue exceeded twelve billion dollars, with a loss of $1b.'
-        ]
-    }
-    response = client.post('/ner', json=body)
+
+def test_ner_sense2vec_enabled():
+    response = client.post('/ner', json=ner_sense2vec_body)
     assert response.status_code == 200
-    with open('src/outputs/ner.json') as f:
+    with open('src/outputs/ner/sense2vec_enabled.json') as f:
         assert response.json() == json.load(f)
 
 
+def test_ner_sense2vec_disabled():
+    response = client.post('/ner', json=ner_body)
+    with open('src/outputs/ner/sense2vec_disabled.json') as f:
+        assert response.json() == json.load(f)
+
+
+def test_ner_spacy_fail():
+    fail('/ner', ner_body, 'ner')
+
+
+def test_ner_sense2vec_fail():
+    fail('/ner', ner_sense2vec_body, 'sense2vec')
+
+
+pos_body = {'text': 'Apple is looking at buying U.K. startup for $1 billion'}
+
+
 def test_pos():
-    text = {'text': 'Apple is looking at buying U.K. startup for $1 billion'}
-    response = client.post('/pos', json=text)
+    response = client.post('/pos', json=pos_body)
     assert response.status_code == 200
     with open('src/outputs/pos.json') as f:
         assert response.json() == json.load(f)
 
 
+def test_pos_fail():
+    fail('/pos', pos_body, 'parser')
+
+
 def test_tokenizer():
     text = {'text': 'Apple is looking at buying U.K. startup for $1 billion'}
     response = client.post('/tokenizer', json=text)
@@ -36,16 +58,29 @@ def test_tokenizer():
         assert response.json() == json.load(f)
 
 
+sentencizer_body = {
+    'text': 'Apple is looking at buying U.K. startup for $1 billion. Another '
+            + 'sentence.'
+}
+
+
 def test_sentencizer():
-    body = {
-        'text': 'Apple is looking at buying U.K. startup for $1 billion. '
-                + 'Another sentence.'
-    }
-    response = client.post('/sentencizer', json=body)
+    response = client.post('/sentencizer', json=sentencizer_body)
     assert response.status_code == 200
     with open('src/outputs/sentencizer.json') as f:
         assert response.json() == json.load(f)
 
 
+def test_sentencizer_fail():
+    fail('/sentencizer', sentencizer_body, 'parser')
+
+
 def test_health_check():
     assert client.get('/health_check').status_code == 204
+
+
+def fail(endpoint, body, pipe):
+    with main.nlp.disable_pipes(pipe):
+        response = client.post(endpoint, json=body)
+        assert response.status_code == 400
+        assert 'detail' in response.json()