--- a
+++ b/ehrkit/solr_lib.py
@@ -0,0 +1,94 @@
+import requests
+import logging
+logger = logging.getLogger(__name__)
+from nltk.stem import WordNetLemmatizer
+lemmatizer = WordNetLemmatizer()
+
+def solr_escape(query: str) -> str:
+    # These special Solr characters need to be escaped. We deal with some of them
+    # "+ - && || ! ( ) { } [ ] ^ " ~ * ? : \ /"
+    char_translation_table = str.maketrans({
+        '[': '',
+        ']': '',
+        '{': '',
+        '}': '',
+        '^': '',
+        '~': '',
+        '*': '',
+        '\\': '',
+        '/': '',
+        '"': '',
+        '!': '\!',
+        '?': '\?',
+        ':': '\:',
+    })
+    return query.translate(char_translation_table)
+
+def get_solr_response_generic(solr_formatted_query: str, solr_core_name: str):
+    solr_response_json = requests.get(
+        url ='http://tangra.cs.yale.edu:8983/solr/{}/select?'.format(solr_core_name),
+        params={
+            'indent': 'on',
+            'q': solr_formatted_query,
+            'rows': '100',
+            'wt': 'json',
+            'fl': 'id, score'
+        }
+    ).json()
+    solr_response = solr_response_json['response']
+    num_rows = solr_response['numFound']
+    rows = solr_response['docs']
+    solr_matched_ids = []
+    id_to_score_map = {}
+    for row in rows:
+        item_id = int(row['id'])
+        item_solr_score = float(row['score'])
+        solr_matched_ids.append(item_id)
+        id_to_score_map[item_id] = item_solr_score
+
+    return solr_matched_ids, id_to_score_map
+def get_solr_response_mimic(raw_query):
+    escaped_query = solr_escape(raw_query)
+    query_words = ['"' + lemmatizer.lemmatize(word) + '"' for word in escaped_query.split()]
+    if len(query_words) > 0:
+            query = ' AND '.join(query_words)
+            solr_formatted_query = 'abbreviations:({}) OR abbreviations_sent_id:({}) OR doctext_not_stored:({})'.format(
+                query, query, query)
+    else:
+        solr_formatted_query = '*:*'
+
+    return get_solr_response_generic(solr_formatted_query, 'ehr_abbs_mimic')
+def get_solr_response_umn_wrap(raw_query):
+    escaped_query = solr_escape(raw_query)
+    query_words = ['"' + lemmatizer.lemmatize(word) + '"' for word in escaped_query.split()]
+    if len(query_words) > 0:
+            query = ' AND '.join(query_words)
+            solr_formatted_query = 'short_form:({})'.format(
+                query)
+    else:
+        solr_formatted_query = '*:*'
+
+    return get_solr_response_umn(solr_formatted_query, 'ehr_abbsense_umn')
+
+def get_solr_response_umn(solr_formatted_query: str, solr_core_name: str):
+    solr_response_json = requests.get(
+        url ='http://tangra.cs.yale.edu:8983/solr/{}/select?'.format(solr_core_name),
+        params={
+            'indent': 'on',
+            'q': solr_formatted_query,
+            'rows': '100',
+            'wt': 'json',
+            'fl': 'id, long_form, score'
+        }
+    ).json()
+    solr_response = solr_response_json['response']
+    num_rows = solr_response['numFound']
+    rows = solr_response['docs']
+    solr_matched_longforms = []
+    long_form_to_score_map = {}
+    for row in rows:
+        item = row['long_form']
+        item_solr_score = float(row['score'])
+        solr_matched_longforms.append(item)
+        long_form_to_score_map[item] = item_solr_score
+    return solr_matched_longforms, long_form_to_score_map