Merge pull request #88 from CDU-data-science-team/0.5.1

0.5.1

.gitignore

@@ -9,3 +9,4 @@ dist/
 .vscode/
 datasets/hidden/*
 test_multilabel/*
+.env

api/api.py

@@ -1,46 +1,141 @@
+import os
 import pickle
 from typing import List
 
 import pandas as pd
 from fastapi import FastAPI
-from pydantic import BaseModel
+from pydantic import BaseModel, validator
 
-from pxtextmining.factories.factory_predict_unlabelled_text import \
-    predict_multilabel_sklearn
+from pxtextmining.factories.factory_predict_unlabelled_text import (
+    predict_multilabel_sklearn,
+)
 
+description = """
+This API is for classifying patient experience qualitative data,
+utilising the models trained as part of the pxtextmining project.
+"""
+
+tags_metadata = [
+    {"name": "index", "description": "Basic page to test if API is working."},
+    {
+        "name": "predict",
+        "description": "Generate multilabel predictions for given text.",
+    },
+]
+
+
+class Test(BaseModel):
+    test: str
+
+    class Config:
+        schema_extra = {
+            "example": {
+                "test": "Hello"
+            }
+        }
 
 class ItemIn(BaseModel):
     comment_id: str
     comment_text: str
+    question_type: str
+
+    class Config:
+        schema_extra = {
+            "example": {
+                "comment_id": "01",
+                "comment_text": "Nurses were friendly. Parking was awful.",
+                "question_type": "nonspecific",
+            }
+        }
 
-app = FastAPI()
+    @validator("question_type")
+    def question_type_validation(cls, v):
+        if v not in ["what_good", "could_improve", "nonspecific"]:
+            raise ValueError(
+                "question_type must be one of what_good, could_improve, or nonspecific"
+            )
+        return v
+
+
+class ItemOut(BaseModel):
+    comment_id: str
+    comment_text: str
+    labels: list
 
-@app.get('/')
+    class Config:
+        schema_extra = {
+            "example": {
+                "comment_id": "01",
+                "comment_text": "Nurses were friendly. Parking was awful.",
+                "labels": ["Staff manner & personal attributes", "Parking"],
+            }
+        }
+
+
+app = FastAPI(
+    title="pxtextmining API",
+    description=description,
+    version="0.0.1",
+    contact={
+        "name": "Patient Experience Qualitative Data Categorisation",
+        "url": "https://cdu-data-science-team.github.io/PatientExperience-QDC/",
+        "email": "[email protected]",
+    },
+    license_info={
+        "name": "MIT License",
+        "url": "https://github.com/CDU-data-science-team/pxtextmining/blob/main/LICENSE",
+    },
+    openapi_tags=tags_metadata
+)
+
+
+@app.get("/", response_model=Test, tags=['index'])
 def index():
-    return {'Test': 'Hello'}
+    return {"test": "Hello"}
 
-@app.post('/predict_multilabel')
+
+@app.post("/predict_multilabel", response_model=List[ItemOut], tags=['predict'])
 def predict(items: List[ItemIn]):
-    """Accepts comment ids and comment text as JSON in a POST request. Makes predictions using
+    """Accepts comment ids, comment text and question type as JSON in a POST request. Makes predictions using trained SVC model.
 
     Args:
-        items (List[ItemIn]): JSON list of dictionaries with the following compulsory keys: `comment_id` (str) and `comment_text` (str). For example, `[{'comment_id': '1', 'comment_text': 'Thank you'}, {'comment_id': '2', 'comment_text': 'Food was cold'}]`
+        items (List[ItemIn]): JSON list of dictionaries with the following compulsory keys:
+        - `comment_id` (str)
+        - `comment_text` (str)
+        - `question_type` (str)
+        The 'question_type' must be one of three values: 'nonspecific', 'what_good', and 'could_improve'.
+        For example, `[{'comment_id': '1', 'comment_text': 'Thank you', 'question_type': 'what_good'},
+        {'comment_id': '2', 'comment_text': 'Food was cold', 'question_type': 'could_improve'}]`
 
     Returns:
-        (dict): Dict containing two keys. `comments_labelled` is a list of dictionaries containing the received comment ids, comment text, and predicted labels. `comment_ids_failed` is a list of the comment_ids where the text was unable to be labelled, for example due to being an empty string, or a null value.
+        (dict): Keys are: `comment_id`, `comment_text`, and predicted `labels`.
     """
-    with open('current_best_multilabel/svc_text_only.sav', 'rb') as model:
-        loaded_model = pickle.load(model)
+
+    # Process received data
     df = pd.DataFrame([i.dict() for i in items], dtype=str)
-    df_newindex = df.set_index('comment_id')
-    df_newindex.index.rename('Index', inplace = True)
-    text_to_predict = df_newindex['comment_text']
-    preds_df = predict_multilabel_sklearn(text_to_predict, loaded_model)
-    preds_df['comment_id'] = preds_df.index.astype(str)
-    merged = pd.merge(df, preds_df, how='left', on='comment_id')
-    merged['labels'] = merged['labels'].fillna('').apply(list)
-    for i in merged['labels'].index:
-        if len(merged['labels'].loc[i]) < 1:
-            merged['labels'].loc[i].append('Labelling not possible')
-    return_dict = merged[['comment_id', 'comment_text', 'labels']].to_dict(orient='records')
+    df_newindex = df.set_index("comment_id")
+    if df_newindex.index.duplicated().sum() != 0:
+        raise ValueError("comment_id must all be unique values")
+    df_newindex.index.rename("Comment ID", inplace=True)
+    text_to_predict = df_newindex[["comment_text", "question_type"]]
+    text_to_predict = text_to_predict.rename(
+        columns={"comment_text": "FFT answer", "question_type": "FFT_q_standardised"}
+    )
+    # Make predictions
+    model_path = os.path.join("api", "svc_minorcats_v5.sav")
+    with open(model_path, "rb") as model:
+        loaded_model = pickle.load(model)
+    preds_df = predict_multilabel_sklearn(
+        text_to_predict, loaded_model, additional_features=True
+    )
+    # Join predicted labels with received data
+    preds_df["comment_id"] = preds_df.index.astype(str)
+    merged = pd.merge(df, preds_df, how="left", on="comment_id")
+    merged["labels"] = merged["labels"].fillna("").apply(list)
+    for i in merged["labels"].index:
+        if len(merged["labels"].loc[i]) < 1:
+            merged["labels"].loc[i].append("Labelling not possible")
+    return_dict = merged[["comment_id", "comment_text", "labels"]].to_dict(
+        orient="records"
+    )
     return return_dict

api/requirements.txt

@@ -0,0 +1,104 @@
+absl-py==1.4.0 ; python_version >= "3.8" and python_version < "3.11"
+anyio==3.6.2 ; python_version >= "3.8" and python_version < "3.11"
+astunparse==1.6.3 ; python_version >= "3.8" and python_version < "3.11"
+attrs==22.2.0 ; python_version >= "3.8" and python_version < "3.11"
+blis==0.7.9 ; python_version >= "3.8" and python_version < "3.11"
+cachetools==5.3.0 ; python_version >= "3.8" and python_version < "3.11"
+catalogue==2.0.8 ; python_version >= "3.8" and python_version < "3.11"
+certifi==2022.12.7 ; python_version >= "3.8" and python_version < "3.11"
+chardet==4.0.0 ; python_version >= "3.8" and python_version < "3.11"
+click==8.1.3 ; python_version >= "3.8" and python_version < "3.11"
+colorama==0.4.6 ; python_version >= "3.8" and python_version < "3.11" and sys_platform == "win32" or python_version >= "3.8" and python_version < "3.11" and platform_system == "Windows"
+confection==0.0.4 ; python_version >= "3.8" and python_version < "3.11"
+contourpy==1.0.7 ; python_version >= "3.8" and python_version < "3.11"
+cycler==0.11.0 ; python_version >= "3.8" and python_version < "3.11"
+cymem==2.0.7 ; python_version >= "3.8" and python_version < "3.11"
+exceptiongroup==1.1.1 ; python_version >= "3.8" and python_version < "3.11"
+fastapi==0.94.1 ; python_version >= "3.8" and python_version < "3.11"
+filelock==3.10.7 ; python_version >= "3.8" and python_version < "3.11"
+flatbuffers==23.3.3 ; python_version >= "3.8" and python_version < "3.11"
+fonttools==4.39.2 ; python_version >= "3.8" and python_version < "3.11"
+gast==0.4.0 ; python_version >= "3.8" and python_version < "3.11"
+google-auth-oauthlib==0.4.6 ; python_version >= "3.8" and python_version < "3.11"
+google-auth==2.16.3 ; python_version >= "3.8" and python_version < "3.11"
+google-pasta==0.2.0 ; python_version >= "3.8" and python_version < "3.11"
+grpcio==1.53.0 ; python_version >= "3.8" and python_version < "3.11"
+h11==0.14.0 ; python_version >= "3.8" and python_version < "3.11"
+h5py==3.8.0 ; python_version >= "3.8" and python_version < "3.11"
+httpcore==0.16.3 ; python_version >= "3.8" and python_version < "3.11"
+httpx==0.23.3 ; python_version >= "3.8" and python_version < "3.11"
+huggingface-hub==0.13.3 ; python_version >= "3.8" and python_version < "3.11"
+idna==2.10 ; python_version >= "3.8" and python_version < "3.11"
+importlib-metadata==6.1.0 ; python_version >= "3.8" and python_version < "3.10"
+importlib-resources==5.12.0 ; python_version >= "3.8" and python_version < "3.10"
+iniconfig==2.0.0 ; python_version >= "3.8" and python_version < "3.11"
+jax==0.4.7 ; python_version >= "3.8" and python_version < "3.11"
+jinja2==3.1.2 ; python_version >= "3.8" and python_version < "3.11"
+joblib==1.2.0 ; python_version >= "3.8" and python_version < "3.11"
+keras==2.12.0 ; python_version >= "3.8" and python_version < "3.11"
+kiwisolver==1.4.4 ; python_version >= "3.8" and python_version < "3.11"
+langcodes==3.3.0 ; python_version >= "3.8" and python_version < "3.11"
+libclang==16.0.0 ; python_version >= "3.8" and python_version < "3.11"
+markdown==3.3.7 ; python_version >= "3.8" and python_version < "3.11"
+markupsafe==2.1.2 ; python_version >= "3.8" and python_version < "3.11"
+matplotlib==3.7.1 ; python_version >= "3.8" and python_version < "3.11"
+ml-dtypes==0.0.4 ; python_version >= "3.8" and python_version < "3.11"
+murmurhash==1.0.9 ; python_version >= "3.8" and python_version < "3.11"
+numpy==1.23.5 ; python_version < "3.11" and python_version >= "3.8"
+oauthlib==3.2.2 ; python_version >= "3.8" and python_version < "3.11"
+opt-einsum==3.3.0 ; python_version >= "3.8" and python_version < "3.11"
+packaging==23.0 ; python_version >= "3.8" and python_version < "3.11"
+pandas==1.5.3 ; python_version >= "3.8" and python_version < "3.11"
+pathy==0.10.1 ; python_version >= "3.8" and python_version < "3.11"
+pillow==9.4.0 ; python_version >= "3.8" and python_version < "3.11"
+pluggy==1.0.0 ; python_version >= "3.8" and python_version < "3.11"
+preshed==3.0.8 ; python_version >= "3.8" and python_version < "3.11"
+protobuf==4.22.1 ; python_version >= "3.8" and python_version < "3.11"
+pyasn1-modules==0.2.8 ; python_version >= "3.8" and python_version < "3.11"
+pyasn1==0.4.8 ; python_version >= "3.8" and python_version < "3.11"
+pydantic==1.10.7 ; python_version >= "3.8" and python_version < "3.11"
+pyparsing==3.0.9 ; python_version >= "3.8" and python_version < "3.11"
+pytest==7.2.2 ; python_version >= "3.8" and python_version < "3.11"
+python-dateutil==2.8.2 ; python_version >= "3.8" and python_version < "3.11"
+pytz==2023.2 ; python_version >= "3.8" and python_version < "3.11"
+pyyaml==6.0 ; python_version >= "3.8" and python_version < "3.11"
+regex==2023.3.23 ; python_version >= "3.8" and python_version < "3.11"
+requests-oauthlib==1.3.1 ; python_version >= "3.8" and python_version < "3.11"
+requests==2.25.1 ; python_version >= "3.8" and python_version < "3.11"
+rfc3986[idna2008]==1.5.0 ; python_version >= "3.8" and python_version < "3.11"
+rsa==4.9 ; python_version >= "3.8" and python_version < "3.11"
+scikit-learn==1.0.2 ; python_version >= "3.8" and python_version < "3.11"
+scipy==1.10.1 ; python_version >= "3.8" and python_version < "3.11"
+setuptools-scm==7.1.0 ; python_version >= "3.8" and python_version < "3.11"
+setuptools==67.6.1 ; python_version >= "3.8" and python_version < "3.11"
+six==1.16.0 ; python_version >= "3.8" and python_version < "3.11"
+smart-open==6.3.0 ; python_version >= "3.8" and python_version < "3.11"
+sniffio==1.3.0 ; python_version >= "3.8" and python_version < "3.11"
+spacy-legacy==3.0.12 ; python_version >= "3.8" and python_version < "3.11"
+spacy-loggers==1.0.4 ; python_version >= "3.8" and python_version < "3.11"
+spacy==3.5.1 ; python_version >= "3.8" and python_version < "3.11"
+srsly==2.4.6 ; python_version >= "3.8" and python_version < "3.11"
+starlette==0.26.1 ; python_version >= "3.8" and python_version < "3.11"
+tensorboard-data-server==0.7.0 ; python_version >= "3.8" and python_version < "3.11"
+tensorboard-plugin-wit==1.8.1 ; python_version >= "3.8" and python_version < "3.11"
+tensorboard==2.12.0 ; python_version >= "3.8" and python_version < "3.11"
+tensorflow-estimator==2.12.0 ; python_version >= "3.8" and python_version < "3.11"
+tensorflow-io-gcs-filesystem==0.31.0 ; python_version >= "3.8" and python_version < "3.11" and platform_machine != "arm64" or python_version >= "3.8" and python_version < "3.11" and platform_system != "Darwin"
+tensorflow==2.12.0 ; python_version >= "3.8" and python_version < "3.11"
+termcolor==2.2.0 ; python_version >= "3.8" and python_version < "3.11"
+thinc==8.1.9 ; python_version >= "3.8" and python_version < "3.11"
+threadpoolctl==3.1.0 ; python_version >= "3.8" and python_version < "3.11"
+tokenizers==0.13.2 ; python_version >= "3.8" and python_version < "3.11"
+tomli==2.0.1 ; python_version >= "3.8" and python_version < "3.11"
+tqdm==4.65.0 ; python_version >= "3.8" and python_version < "3.11"
+transformers==4.27.3 ; python_version >= "3.8" and python_version < "3.11"
+typer==0.7.0 ; python_version >= "3.8" and python_version < "3.11"
+typing-extensions==4.5.0 ; python_version >= "3.8" and python_version < "3.11"
+urllib3==1.26.15 ; python_version >= "3.8" and python_version < "3.11"
+uvicorn==0.20.0 ; python_version >= "3.8" and python_version < "3.11"
+wasabi==1.1.1 ; python_version >= "3.8" and python_version < "3.11"
+werkzeug==2.2.3 ; python_version >= "3.8" and python_version < "3.11"
+wheel==0.40.0 ; python_version >= "3.8" and python_version < "3.11"
+wrapt==1.14.1 ; python_version >= "3.8" and python_version < "3.11"
+zipp==3.15.0 ; python_version >= "3.8" and python_version < "3.10"
+pxtextmining==0.5.1

api/test_api.py

@@ -13,15 +13,24 @@ def test_json_predictions(json):
     response = requests.post("http://127.0.0.1:8000/predict_multilabel", json=json)
     return response
 
+
 if __name__ == "__main__":
-    df = pd.read_csv('datasets/hidden/API_test.csv')
-    df = df[['row_id', 'comment_txt']].copy().set_index('row_id')[:20]
+    df = pd.read_csv("datasets/hidden/API_test.csv")
+    df = df[["row_id", "comment_txt"]].copy().set_index("row_id")[:20]
     js = []
     for i in df.index:
-        js.append({'comment_id': str(i), 'comment_text': df.loc[i]['comment_txt']})
-    print('The JSON that was sent looks like:')
+        js.append(
+            {
+                "comment_id": str(i),
+                "comment_text": df.loc[i]["comment_txt"],
+                "question_type": "nonspecific",
+            }
+        )
+    print("The JSON that was sent looks like:")
+    print(js[:5])
+    print("The JSON that was sent looks like:")
     print(js[:5])
-    print('The JSON that is returned is:')
+    print("The JSON that is returned is:")
     returned_json = test_json_predictions(js).json()
     print(returned_json)
     # json_object = json.dumps(returned_json, indent=4)