Upload database.py

database.py

@@ -0,0 +1,67 @@
+import json
+import os
+import random
+from fuzzywuzzy import fuzz
+from itertools import chain
+from zipfile import ZipFile
+from copy import deepcopy
+from convlab.util.unified_datasets_util import BaseDatabase, download_unified_datasets
+
+
+class Database(BaseDatabase):
+    def __init__(self):
+        """extract data.zip and load the database."""
+        data_path = download_unified_datasets('camrest', 'data.zip', os.path.dirname(os.path.abspath(__file__)))
+        archive = ZipFile(data_path)
+        self.dbs = {}
+        with archive.open('data/CamRestDB.json') as f:
+            self.dbs['restaurant'] = json.loads(f.read())
+        self.slot2dbattr = {
+            'price range': 'pricerange',
+        }
+
+    def query(self, domain: str, state: dict, topk: int, ignore_open=False, soft_contraints=(), fuzzy_match_ratio=60) -> list:
+        """return a list of topk entities (dict containing slot-value pairs) for a given domain based on the dialogue state."""
+        # query the db
+        assert domain == 'restaurant'
+        state = list(map(lambda ele: (self.slot2dbattr.get(ele[0], ele[0]), ele[1]) if not(ele[0] == 'area' and ele[1] == 'center') else ('area', 'centre'), state))
+
+        found = []
+        for i, record in enumerate(self.dbs[domain]):
+            constraints_iterator = zip(state, [False] * len(state))
+            soft_contraints_iterator = zip(soft_contraints, [True] * len(soft_contraints))
+            for (key, val), fuzzy_match in chain(constraints_iterator, soft_contraints_iterator):
+                if val in ["", "dont care", 'not mentioned', "don't care", "dontcare", "do n't care"]:
+                    pass
+                else:
+                    try:
+                        if key not in record:
+                            continue
+                        if record[key].strip() == '?':
+                            # '?' matches any constraint
+                            continue
+                        else:
+                            if not fuzzy_match:
+                                if val.strip().lower() != record[key].strip().lower():
+                                    break
+                            else:
+                                if fuzz.partial_ratio(val.strip().lower(), record[key].strip().lower()) < fuzzy_match_ratio:
+                                    break
+                    except:
+                        continue
+            else:
+                res = deepcopy(record)
+                res['Ref'] = '{0:08d}'.format(i)
+                found.append(res)
+                if len(found) == topk:
+                    return found
+        return found
+
+
+if __name__ == '__main__':
+    db = Database()
+    assert issubclass(Database, BaseDatabase)
+    assert isinstance(db, BaseDatabase)
+    res = db.query("restaurant", [['price range', 'expensive']], topk=3)
+    print(res, len(res))
+    # print(db.query("hotel", [['price range', 'moderate'], ['stars','4'], ['type', 'guesthouse'], ['internet', 'yes'], ['parking', 'no'], ['area', 'east']]))