this only makes sense if we have a target word set, which we usually do.
start with the target word and go backwords, finding k2s that lead to it
(and that lead to that k2, and so on) until we get to the start-of-chain
value, when we know we're done working backwards. then resume the normal
appending logic
probably needs some work, probably a bit slow on huge databases. analysis
pending, but this appears to work
check interval is every 10 minutes, rows in markov_chatter_target
have a 1 in chance chance of leading to a line being generated,
every 10 minutes. (so an interval of 144 = 10 min * 6 * 24 = one line
per day, on average)
Markov, Twitter: switch to forking a thread ourselves, and check every
second whether or not to quit. this is the "better" part above, as
now we can instantly quit the thread rather than waiting for all
the timers to fire and expire
track all lines seen and all lines said by Markov. every 30 seconds,
if there have been more than 20 such lines, and Markov is responsible
for roughly half of them, then shut up for 30 seconds, because the
bot probably got stuck talking to another bot.
this should mean that such a reply infinite loop can't happen for
more than a minute.
i'm not entirely sure on the 30 sec/20 lines ratio. this may need
tuning.
when finding a key for (__start1,__start2), instead of fetcihng all
(which can be a lot, in chatty channels and/or over time), get the
max ID in the table, pick a random ID between 1,max, and pick the
first id >= to it, and use that. just as random, nowhere near as
intensive.
a context is a meta-classification ('banter, 'secrets', whatever)
based on targets (channels or nicknames). when a line is being
learned from a known target, the chains are placed in that context.
this is for allowing one brain to have multiple personalities, in
a sense, for large networks or cases where there may be a more
sanitized set of channels and a couple channels where everyone lets
it rip. a later enhancement would have sentence creation choose from
context-less chains (and contexts matching the current target), but
i need to go back to the drawing board on that one a bit.
ramble ramble ramble
e.g. if i say 'dr_botzo: hello dude', he only learns 'hello dude'.
this is mainly being done because the bot's name being in the brain
so many times was getting kind of silly, especially in channels that
have lots of conversations with the bot
somehow a chain led us down a path where there are no values for
the keys in the chain. if that happens, just abort.
i'm not quite sure how this could happen
the motivation here is doing (foo)++ would match \S+ first, adding
(foo) to the karma database (rather than foo, which is probably what
the user meant)
