basic api #35

README.md

@@ -164,13 +164,13 @@ A complete worfklow is described in our [`examples`](examples) notebook.
 You can deploy a `cdQA` REST API by executing:
 
 ```shell
-python api.py
+FLASK_APP=api.py flask run -h 0.0.0.0
 ```
 
 To try it, execute:
 
 ```shell
-curl http://127.0.0.1:5000/
+http localhost:5000/api q=='your question here'
 ```
 
 If you wish to serve a user interface, follow the instructions of [cdQA-ui](https://github.com/fmikaelian/cdQA-ui), a web interface developed for `cdQA`.

api.py

@@ -1,14 +1,25 @@
-from flask import Flask
-from flask_restful import Resource, Api
+from flask import Flask, request, jsonify
+
+import os
+from ast import literal_eval
+import pandas as pd
+
+from cdqa.utils.converter import filter_paragraphs
+from cdqa.reader.bertqa_sklearn import BertQA
+from cdqa.pipeline.qa_pipeline import QAPipeline
 
 app = Flask(__name__)
-api = Api(app)
 
-class HelloWorld(Resource):
-    def get(self):
-        return {'hello': 'world'}
+df = pd.read_csv('../data/bnpp_newsroom_v1.0/bnpp_newsroom-v1.0.csv', converters={'paragraphs': literal_eval})
+df['paragraphs'] = df['paragraphs'].apply(filter_paragraphs)
+df['content'] = df['paragraphs'].apply(lambda x: ' '.join(x))
 
-api.add_resource(HelloWorld, '/')
+qa_pipe = QAPipeline(model = '../models/bert_qa_squad_vCPU/bert_qa_squad_vCPU-sklearn.joblib')
+qa_pipe.fit(df)
 
-if __name__ == '__main__':
-    app.run(debug=True)
+@app.route('/api', methods=['GET'])
+def api():
+    query = request.query_string
+    prediction = qa_pipe.answer(query)
+    return jsonify(query=query,
+                   prediction=prediction)