Bump PMAT version to 0.9.3, simplify calculate_bet_amount for KnownOutcomeAgent
#51
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- prediction_market_agent/agents/known_outcome_agent/deploy.py (2 hunks)
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prediction_market_agent/agents/known_outcome_agent/deploy.py (1)
85-85: Consider adding a comment explaining the rationale behind using a fixed bet amount and relying onmarket.currencydirectly in thecalculate_bet_amountmethod. This will help maintain clarity and understanding for future maintenance or enhancements.
| ), | ||
| currency=Currency.xDai, | ||
| ) | ||
| return BetAmount(amount=(Decimal(1.0)), currency=market.currency) |
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I know we now filtering for markets with liquidity, but people can still create markets with for example, $0.01 in liquidity and then it doesn't make much sense to me to bet more than the minimal bet. wdyt?
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Good point. In that case, I think it makes sense to filter the market at the pick_markets stage, so as not to waste openai API credits. I've made that change above
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Don't you want to keep them for benchmark purposes?
If not, okay by me, just that
elif market.get_liquidity_in_xdai() > 5:
print(
f"Skipping market {market.id=} {market.question=}, because it has insufficient liquidity."
)
Should it be with the opposite sign, probably?
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Don't you want to keep them for benchmark purposes?
I'm not too concerned about that, more about trying to get the markets that should be p_yes/no==0.95 to that point
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- prediction_market_agent/agents/known_outcome_agent/deploy.py (4 hunks)
- prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py (1 hunks)
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- prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py
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- prediction_market_agent/agents/known_outcome_agent/deploy.py
| @@ -28,14 +27,19 @@ def market_is_saturated(market: AgentMarket) -> bool: | |||
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| class DeployableKnownOutcomeAgent(DeployableAgent): | |||
| model = "gpt-4-1106-preview" | |||
| model = "gpt-4-turbo-preview" | |||
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I just noticed this as well, this can point to a different model in future without notice, is that desirable?
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Hmm good question. Maybe in general not, but I reckon for this case it's good - my reasoning being that otherwise over time the agent will get less and less 'up to date with current events' which I would assume is bad for making future predictions.
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