implemented a basic api used by the nlp rest service

.dockerignore

@@ -0,0 +1,5 @@
+*.DS_Store
+.git
+.idea
+.dat
+venv

.gitignore

@@ -11,6 +11,8 @@ tmp/
 *_tmp/
 medcat.egg-info/
 build/
+.idea
+venv
 
 #tmp and similar files
 .nfs*
@@ -29,3 +31,7 @@ tmp_*
 *hidden*
 nohup.out
 tmp.py
+.DS_Store
+
+# models files
+*.dat

api/cogstack_api.py

@@ -0,0 +1,132 @@
+from flask import Flask
+from flask import Response
+import json
+from medcat.cdb import CDB
+from medcat.utils.vocab import Vocab
+from medcat.cat import CAT
+from flask import request
+import os
+
+
+vocab = Vocab()
+cdb = CDB()
+
+cdb.load_dict(os.getenv("UMLS_MODEL", '/cat/models/med_ann_norm.dat'))
+vocab.load_dict(path=os.getenv("VOCAB_MODEL", '/cat/models/med_ann_norm_dict.dat'))
+cat = CAT(cdb, vocab=vocab)
+
+cat.spacy_cat.train = False
+
+app = Flask(__name__)
+
+
+app_name = 'MEDCAT'
+app_lang = 'en'
+app_version = os.getenv("CAT_VERSION", '0.1.0')
+
+
+@app.route('/api/info', methods=['GET'])
+def info():
+    app_info = {'name': app_name,
+                'language': app_lang,
+                'version': app_version}
+    return Response(response=json.dumps(app_info), status=200, mimetype="application/json")
+
+
+@app.route('/api/process', methods=['POST'])
+def process():
+    payload = request.get_json()
+    if payload is None or not is_request_payload_valid(payload):
+        return Response(response="Input Payload should be JSON", status=400)
+
+    try:
+        result = process_request_payload(payload)
+        response = {'result': result}
+        return Response(response=json.dumps(response), status=200)
+
+    except Exception as e:
+        Response(response="Internal processing error %d" % e, status=500)
+
+
+@app.route('/api/process_bulk', methods=['POST'])
+def process_bulk():
+    payload = request.get_json()
+    if payload is None or not is_request_payload_valid_bulk(payload):
+        return Response(response="Input Payload should be JSON", status=400)
+
+    try:
+        result = process_request_payload_bulk(payload)
+        response = {'result': result}
+        return Response(response=json.dumps(response), status=200)
+
+    except Exception as e:
+        Response(response="Internal processing error %d" % e, status=500)
+
+
+def is_request_payload_valid(payload):
+    if 'content' not in payload or 'text' not in payload['content']:
+        return False
+    return True
+
+
+def process_request_payload(payload):
+    text = payload['content']['text']
+    entities = cat.get_entities(text)
+
+    # parse the result
+    nlp_result = {'text': text,
+                  'annotations': entities,
+                  'success': True
+                  }
+
+    # append footer
+    if 'footer' in payload['content']:
+        nlp_result['footer'] = payload['content']['footer']
+
+    return nlp_result
+
+
+def is_request_payload_valid_bulk(payload):
+    if 'content' not in payload:
+        return False
+    return True
+
+
+def process_request_payload_bulk(payload):
+
+    # prepare the payload
+    content = payload['content']
+    documents = [(i, content[i]['text']) for i in range(len(content))]
+
+    nproc = int(os.getenv('NPROC', 8))
+    batch_size = min(300, int(len(documents) / (2 * nproc)))
+    res_raw = cat.multi_processing(documents, nproc=nproc, batch_size=batch_size)
+
+    assert len(res_raw) == len(payload['content'])
+
+    # parse the result -- need to sort by IDs as there's no guarantee
+    # on the order of the docs processed
+    res_sorted = sorted(res_raw, key=lambda x: x[0])
+    nlp_result = []
+
+    # parse the results and add footer if needed
+    for i in range(len(res_sorted)):
+        res = res_sorted[i]
+        in_ct = content[i]
+
+        # parse the result
+        out_res = {'text': res[1]["text"],
+                   'annotations': res[1]["entities"],
+                   'success': True
+                   }
+        # append the footer
+        if 'footer' in in_ct:
+            out_res['footer'] = in_ct['footer']
+
+        nlp_result.append(out_res)
+
+    return nlp_result
+
+
+if __name__ == '__main__':
+    app.run(debug=True, host='0.0.0.0', port=5000)