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authorVsevolod Stakhov <vsevolod@rspamd.com>2023-12-07 15:01:11 +0000
committerVsevolod Stakhov <vsevolod@rspamd.com>2023-12-07 15:01:11 +0000
commit0d993187c1b1b37cfd99d3212745927eea0bff7a (patch)
treedd11da9a27a4c4df441db53370e16850d48e02ea /lualib
parent3a7f4ef0ed9fb2583387c0fbcc7fc28ab403b3bc (diff)
downloadrspamd-0d993187c1b1b37cfd99d3212745927eea0bff7a.tar.gz
rspamd-0d993187c1b1b37cfd99d3212745927eea0bff7a.zip
[Project] Add bayes learn script
Diffstat (limited to 'lualib')
-rw-r--r--lualib/lua_bayes_redis.lua15
-rw-r--r--lualib/redis_scripts/bayes_learn.lua25
2 files changed, 38 insertions, 2 deletions
diff --git a/lualib/lua_bayes_redis.lua b/lualib/lua_bayes_redis.lua
index 575beff4b..2286295d5 100644
--- a/lualib/lua_bayes_redis.lua
+++ b/lualib/lua_bayes_redis.lua
@@ -42,8 +42,19 @@ local function gen_classify_functor(redis_params, classify_script_id)
end
local function gen_learn_functor(redis_params, learn_script_id)
- return function(task, expanded_key, id, is_spam, stat_tokens, callback)
- -- TODO: write this function
+ return function(task, expanded_key, id, is_spam, symbol, is_unlearn, stat_tokens, callback)
+ local function learn_redis_cb(err, data)
+ lua_util.debugm(N, task, 'learn redis cb: %s, %s', err, data)
+ if err then
+ callback(task, false, err)
+ else
+ callback(task, true)
+ end
+ end
+
+ lua_redis.exec_redis_script(learn_script_id,
+ { task = task, is_write = false, key = expanded_key },
+ learn_redis_cb, { expanded_key, is_spam, symbol, is_unlearn, stat_tokens })
end
end
diff --git a/lualib/redis_scripts/bayes_learn.lua b/lualib/redis_scripts/bayes_learn.lua
new file mode 100644
index 000000000..2b74fcca9
--- /dev/null
+++ b/lualib/redis_scripts/bayes_learn.lua
@@ -0,0 +1,25 @@
+-- Lua script to perform bayes learning
+-- This script accepts the following parameters:
+-- key1 - prefix for bayes tokens (e.g. for per-user classification)
+-- key2 - boolean is_spam
+-- key3 - string symbol
+-- key4 - boolean is_unlearn
+-- key5 - set of tokens encoded in messagepack array of int64_t
+
+local prefix = KEYS[1]
+local is_spam = KEYS[2]
+local symbol = KEYS[3]
+local is_unlearn = KEYS[4]
+local input_tokens = cmsgpack.unpack(KEYS[5])
+
+local prefix_underscore = prefix .. '_'
+local hash_key = is_spam and 'S' or 'H'
+local learned_key = is_spam and 'learns_spam' or 'learns_ham'
+
+redis.call('SADD', symbol .. '_keys', prefix)
+redis.call('HSET', prefix, 'version', '2') -- new schema
+redis.call('HINCRBY', prefix, learned_key, is_unlearn and -1 or 1) -- increase or decrease learned count
+
+for _, token in ipairs(input_tokens) do
+ redis.call('HINCRBY', prefix_underscore .. tostring(token), hash_key, 1)
+end \ No newline at end of file