Joblib
English
llm
human-feedback
weak supervision
data filtering
Christopher Glaze commited on
Commit
fbe1af4
·
1 Parent(s): 9067c0f

Update data contract

Browse files
Files changed (2) hide show
  1. handler.py +13 -4
  2. tests.py +20 -2
handler.py CHANGED
@@ -1,5 +1,5 @@
1
 
2
- from typing import Dict, Union, Optional
3
  from pathlib import Path
4
  import json
5
  import joblib
@@ -114,12 +114,19 @@ class EndpointHandler():
114
  return self.response_pipeline.predict_proba(df1)[:,1]
115
 
116
 
117
- def __call__(self, df: Union[pd.DataFrame, Dict]):
118
 
119
- is_dict = isinstance(df, dict)
 
 
 
120
 
121
  if is_dict:
122
- df = pd.DataFrame([df])
 
 
 
 
123
 
124
  if 'dataset' not in df.columns:
125
  df['dataset'] = ''
@@ -135,5 +142,7 @@ class EndpointHandler():
135
 
136
  if is_dict:
137
  return predictions[0]
 
 
138
  else:
139
  return pd.DataFrame(predictions, index=df.index)
 
1
 
2
+ from typing import Dict, List, Union, Optional
3
  from pathlib import Path
4
  import json
5
  import joblib
 
114
  return self.response_pipeline.predict_proba(df1)[:,1]
115
 
116
 
117
+ def __call__(self, data: Dict[str, Union[Dict, List, pd.DataFrame]]):
118
 
119
+ inputs = data['inputs']
120
+
121
+ is_dict = isinstance(inputs, dict)
122
+ is_list = isinstance(inputs, list)
123
 
124
  if is_dict:
125
+ df = pd.DataFrame([inputs])
126
+ elif is_list:
127
+ df = pd.DataFrame(inputs)
128
+ else:
129
+ df = inputs
130
 
131
  if 'dataset' not in df.columns:
132
  df['dataset'] = ''
 
142
 
143
  if is_dict:
144
  return predictions[0]
145
+ elif is_list:
146
+ return predictions
147
  else:
148
  return pd.DataFrame(predictions, index=df.index)
tests.py CHANGED
@@ -1,11 +1,29 @@
1
  from handler import EndpointHandler
 
2
 
3
  # init handler
4
  response_model_handler = EndpointHandler()
5
 
6
  # prepare sample payload
7
- payload = {"instruction": "What are some ways to stay energized throughout the day?",
8
- "response": "Drink lots of coffee!"}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9
 
10
  # test the handler
11
  pred=response_model_handler(payload)
 
1
  from handler import EndpointHandler
2
+ import pandas as pd
3
 
4
  # init handler
5
  response_model_handler = EndpointHandler()
6
 
7
  # prepare sample payload
8
+ payload = {'inputs': {"instruction": "What are some ways to stay energized throughout the day?",
9
+ "response": "Drink lots of coffee!"}}
10
+
11
+ # test the handler
12
+ pred=response_model_handler(payload)
13
+
14
+ print(pred)
15
+
16
+ payload = {'inputs': [{"instruction": "What are some ways to stay energized throughout the day?",
17
+ "response": "Drink lots of coffee!"}]*2}
18
+
19
+ # test the handler
20
+ pred=response_model_handler(payload)
21
+
22
+ print(pred)
23
+
24
+
25
+ payload = {'inputs': pd.DataFrame([{"instruction": "What are some ways to stay energized throughout the day?",
26
+ "response": "Drink lots of coffee!"}]*2)}
27
 
28
  # test the handler
29
  pred=response_model_handler(payload)