1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
|
-- Lua script to perform bayes learning (multi-class)
-- This script accepts the following parameters:
-- key1 - prefix for bayes tokens (e.g. for per-user classification)
-- key2 - class label string (e.g. "S", "H", "T")
-- key3 - string symbol
-- key4 - boolean is_unlearn
-- key5 - set of tokens encoded in messagepack array of strings
-- key6 - set of text tokens (if any) encoded in messagepack array of strings (size must be twice of `KEYS[5]`)
local prefix = KEYS[1]
local class_label = KEYS[2]
local symbol = KEYS[3]
local is_unlearn = KEYS[4] == 'true' and true or false
local input_tokens = cmsgpack.unpack(KEYS[5])
local text_tokens
if KEYS[6] then
text_tokens = cmsgpack.unpack(KEYS[6])
end
-- Handle backward compatibility for boolean values
if class_label == 'true' then
class_label = 'S' -- spam
elseif class_label == 'false' then
class_label = 'H' -- ham
end
local hash_key = class_label
local learned_key = 'learns_' .. string.lower(class_label)
-- Handle legacy keys for backward compatibility
if class_label == 'S' then
learned_key = 'learns_spam'
elseif class_label == 'H' then
learned_key = 'learns_ham'
end
redis.call('SADD', symbol .. '_keys', prefix)
redis.call('HSET', prefix, 'version', '2') -- new schema
-- Update learned count, but prevent it from going negative
if is_unlearn then
local current_count = tonumber(redis.call('HGET', prefix, learned_key)) or 0
if current_count > 0 then
redis.call('HINCRBY', prefix, learned_key, -1)
end
else
redis.call('HINCRBY', prefix, learned_key, 1)
end
for i, token in ipairs(input_tokens) do
-- Update token count, but prevent it from going negative
if is_unlearn then
local current_token_count = tonumber(redis.call('HGET', token, hash_key)) or 0
if current_token_count > 0 then
redis.call('HINCRBY', token, hash_key, -1)
end
else
redis.call('HINCRBY', token, hash_key, 1)
end
if text_tokens then
local tok1 = text_tokens[i * 2 - 1]
local tok2 = text_tokens[i * 2]
if tok1 then
if tok2 then
redis.call('HSET', token, 'tokens', string.format('%s:%s', tok1, tok2))
else
redis.call('HSET', token, 'tokens', tok1)
end
if is_unlearn then
local current_z_score = tonumber(redis.call('ZSCORE', prefix .. '_z', token)) or 0
if current_z_score > 0 then
redis.call('ZINCRBY', prefix .. '_z', -1, token)
end
else
redis.call('ZINCRBY', prefix .. '_z', 1, token)
end
end
end
end
|
