api.py

app.py

@@ -0,0 +1,124 @@
+from flask import Flask,request,jsonify,Blueprint,session,render_template,Response
+import spacy
+import numpy as np
+from sentence_transformers import SentenceTransformer,util
+from elasticsearch import Elasticsearch
+#bp = Blueprint('bp', __name__)   
+
+app=Flask(__name__)
+
+
+
+def similarity(model,vertical):
+    vertical_list = ["Mortgage","Real estate","Retail","Insurance","Human_Resource","Pharmaceutical"]
+    word_embeddings = model.encode(vertical_list, convert_to_tensor=True)
+    user_embedding = model.encode(vertical, convert_to_tensor=True)
+    cosine_similarities = util.pytorch_cos_sim(user_embedding, word_embeddings)
+    most_similar_word_index = np.argmax(cosine_similarities)
+    most_similar_word = vertical_list[most_similar_word_index]
+    return most_similar_word
+
+
+
+def get_entities(text):
+    ner_model=spacy.load("spacy_ner_model/en_pipeline/en_pipeline-0.0.0")
+    sim_model=SentenceTransformer("sentence_transformer_model")
+
+    doc = ner_model(text)
+
+    city = None
+    vertical = None
+    zip_code = None
+    state = None
+    state_code = None
+
+    entity_variables = {
+        'CITY': 'city',
+        'VERTICAL': 'vertical',
+        'ZIPCODE': 'zip_code',
+        'STATE': 'state',
+        'STATE_CODE': 'state_code'
+    }
+
+    entity_values = {var: None for var in entity_variables.values()}
+
+    for ent in doc.ents:
+        label = ent.label_
+        if label in entity_variables:
+            var_name = entity_variables[label]
+            var_value = ent.text
+            if var_name == 'vertical':
+                if entity_values[var_name] is None or len(var_value) < len(entity_values[var_name]):
+                    entity_values[var_name] = var_value
+            else:
+                entity_values[var_name] = var_value
+
+
+    city = entity_values['city']
+    if entity_values['vertical']:
+        vertical=similarity(sim_model,entity_values['vertical'])
+    else:
+        vertical = None
+    zip_code = entity_values['zip_code']
+    state = entity_values['state']
+    state_code = entity_values['state_code']
+
+
+    should_clauses = []
+    fields_with_values = []
+    fields = [
+        ("city", city),
+        ("vertical", vertical),
+        ("zip_code", zip_code),
+        ("state", state),
+        ("state_code", state_code)
+    ]
+
+    for field, value in fields:
+        if value is not None:
+            should_clause = {
+                "match": {
+                    field: value
+                }
+            }
+            should_clauses.append(should_clause)
+            fields_with_values.append(field)
+            fields_with_values.append("name")
+
+    query = {
+        'query': {
+            "bool": {
+                "must": should_clauses
+            }
+            
+        }
+    }
+
+    return query,fields_with_values
+
+
+
+@app.route('/search',methods=["GET"])
+def search():
+    text = request.args.get("text")
+    #text=request.get_json()["text"]
+
+    #http://127.0.0.1:5000/search?text=give%20me%20best%20loan%20agents%20in%20Chicago
+    query,fields_with_values=get_entities(text)
+    ELASTIC_PASSWORD = "tILF0omcl27kdZ2G7sFZ3SGf"
+    es = Elasticsearch(["https://elasticsearch.preprod.experience.com:443"], basic_auth=("elastic_app_user", ELASTIC_PASSWORD), verify_certs= True)
+    results = es.search(index='profiles_phase2', body=query, track_total_hits=True, source=fields_with_values)
+    l=[]
+    for hit in results['hits']['hits']:
+        source = hit['_source']
+        l.append(source)
+    print("hai")
+    return jsonify(l)
+
+
+
+
+if __name__=="__main__":
+    with app.app_context():
+        #app.register_blueprint(bp)
+        app.run()