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Allow to submit job results #541

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merged 5 commits into from
Nov 4, 2024
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Allow to submit job results #541

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d9b4df7
Allow to submit job results
kongzii Nov 1, 2024
4f202e7
small refac
kongzii Nov 1, 2024
9bb8774
fixes
kongzii Nov 1, 2024
20ccce1
missing abstractmehod
kongzii Nov 1, 2024
92db034
add check
kongzii Nov 1, 2024
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45 changes: 0 additions & 45 deletions prediction_market_agent_tooling/jobs/jobs.py
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17 changes: 16 additions & 1 deletion prediction_market_agent_tooling/jobs/jobs_models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,12 @@

from pydantic import BaseModel

from prediction_market_agent_tooling.markets.agent_market import AgentMarket
from prediction_market_agent_tooling.deploy.betting_strategy import ProbabilisticAnswer
from prediction_market_agent_tooling.gtypes import Probability
from prediction_market_agent_tooling.markets.agent_market import (
AgentMarket,
ProcessedTradedMarket,
)
from prediction_market_agent_tooling.markets.omen.omen_subgraph_handler import (
FilterBy,
SortBy,
Expand Down Expand Up @@ -43,6 +48,10 @@ def get_jobs(
) -> t.Sequence["JobAgentMarket"]:
"""Get all available jobs."""

@abstractmethod
def submit_job_result(self, max_bond: float, result: str) -> ProcessedTradedMarket:
"""Submit the completed result for this job."""

def to_simple_job(self, max_bond: float) -> SimpleJob:
return SimpleJob(
id=self.id,
Expand All @@ -51,3 +60,9 @@ def to_simple_job(self, max_bond: float) -> SimpleJob:
currency=self.currency.value,
deadline=self.deadline,
)

def get_job_answer(self, result: str) -> ProbabilisticAnswer:
# Just return 100% yes with 100% confidence, because we assume the job is completed correctly.
return ProbabilisticAnswer(
p_yes=Probability(1.0), confidence=1.0, reasoning=result
)
Comment on lines +72 to +76
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⚠️ Potential issue

Add basic validation for job result

The method assumes 100% confidence without validating the result. Consider adding basic validation to ensure the result is not empty or malformed before assuming perfect confidence.

     def get_job_answer(self, result: str) -> ProbabilisticAnswer:
+        if not result or not result.strip():
+            raise ValueError("Job result cannot be empty")
+
         # Just return 100% yes with 100% confidence, because we assume the job is completed correctly.
         return ProbabilisticAnswer(
             p_yes=Probability(1.0), confidence=1.0, reasoning=result
         )
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
def get_job_answer(self, result: str) -> ProbabilisticAnswer:
# Just return 100% yes with 100% confidence, because we assume the job is completed correctly.
return ProbabilisticAnswer(
p_yes=Probability(1.0), confidence=1.0, reasoning=result
)
def get_job_answer(self, result: str) -> ProbabilisticAnswer:
if not result or not result.strip():
raise ValueError("Job result cannot be empty")
# Just return 100% yes with 100% confidence, because we assume the job is completed correctly.
return ProbabilisticAnswer(
p_yes=Probability(1.0), confidence=1.0, reasoning=result
)

96 changes: 56 additions & 40 deletions prediction_market_agent_tooling/jobs/omen/omen_jobs.py
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Original file line number Diff line number Diff line change
@@ -1,15 +1,14 @@
import typing as t

from web3 import Web3

from prediction_market_agent_tooling.config import APIKeys
from prediction_market_agent_tooling.deploy.betting_strategy import (
Currency,
KellyBettingStrategy,
ProbabilisticAnswer,
TradeType,
)
from prediction_market_agent_tooling.gtypes import Probability
from prediction_market_agent_tooling.jobs.jobs_models import JobAgentMarket
from prediction_market_agent_tooling.markets.agent_market import ProcessedTradedMarket
from prediction_market_agent_tooling.markets.data_models import PlacedTrade, Trade
from prediction_market_agent_tooling.markets.omen.omen import (
BetAmount,
OmenAgentMarket,
Expand All @@ -36,7 +35,20 @@ def deadline(self) -> DatetimeUTC:
return self.close_time

def get_reward(self, max_bond: float) -> float:
return compute_job_reward(self, max_bond)
trade = self.get_job_trade(
max_bond,
result="", # Pass empty result, as we are computing only potential reward at this point.
)
reward = (
self.get_buy_token_amount(
bet_amount=BetAmount(
amount=trade.amount.amount, currency=trade.amount.currency
),
direction=trade.outcome,
).amount
- trade.amount.amount
)
return reward

@classmethod
def get_jobs(
Expand All @@ -50,6 +62,45 @@ def get_jobs(
)
return [OmenJobAgentMarket.from_omen_market(market) for market in markets]

@staticmethod
def get_job(id: str) -> "OmenJobAgentMarket":
return OmenJobAgentMarket.from_omen_agent_market(
OmenJobAgentMarket.get_binary_market(id=id)
)

def submit_job_result(self, max_bond: float, result: str) -> ProcessedTradedMarket:
trade = self.get_job_trade(max_bond, result)
buy_id = self.buy_tokens(outcome=trade.outcome, amount=trade.amount)

processed_traded_market = ProcessedTradedMarket(
answer=self.get_job_answer(result),
trades=[PlacedTrade.from_trade(trade, id=buy_id)],
Comment on lines +84 to +85
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⚠️ Potential issue

Implement the get_job_answer method

The method get_job_answer is called but not implemented in OmenJobAgentMarket. Since it's an abstract method in the base class JobAgentMarket, you need to provide an implementation in this subclass to prevent runtime errors.

Consider adding the following implementation:

def get_job_answer(self, result: str) -> bool:
    # Convert the result string to the expected answer format
    return result.lower() == "yes"

Also applies to: 84-84

)

keys = APIKeys()
self.store_trades(processed_traded_market, keys)

return processed_traded_market

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⚠️ Potential issue

Add error handling for token purchase operation.

The buy_tokens call could fail due to network issues or insufficient funds. Consider adding try-catch block to handle potential errors gracefully.

 def submit_job_result(self, max_bond: float, result: str) -> ProcessedTradedMarket:
     trade = self.get_job_trade(max_bond, result)
-    buy_id = self.buy_tokens(outcome=trade.outcome, amount=trade.amount)
+    try:
+        buy_id = self.buy_tokens(outcome=trade.outcome, amount=trade.amount)
+    except Exception as e:
+        raise ValueError(f"Failed to purchase tokens: {str(e)}") from e
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
def submit_job_result(self, max_bond: float, result: str) -> ProcessedTradedMarket:
trade = self.get_job_trade(max_bond, result)
buy_id = self.buy_tokens(outcome=trade.outcome, amount=trade.amount)
processed_traded_market = ProcessedTradedMarket(
answer=self.get_job_answer(result),
trades=[PlacedTrade.from_trade(trade, id=buy_id)],
)
keys = APIKeys()
self.store_trades(processed_traded_market, keys)
return processed_traded_market
def submit_job_result(self, max_bond: float, result: str) -> ProcessedTradedMarket:
trade = self.get_job_trade(max_bond, result)
try:
buy_id = self.buy_tokens(outcome=trade.outcome, amount=trade.amount)
except Exception as e:
raise ValueError(f"Failed to purchase tokens: {str(e)}") from e
processed_traded_market = ProcessedTradedMarket(
answer=self.get_job_answer(result),
trades=[PlacedTrade.from_trade(trade, id=buy_id)],
)
keys = APIKeys()
self.store_trades(processed_traded_market, keys)
return processed_traded_market

def get_job_trade(self, max_bond: float, result: str) -> Trade:
# Because jobs are powered by prediction markets, potentional reward depends on job's liquidity and our will to bond (bet) our xDai into our job completion.
strategy = KellyBettingStrategy(max_bet_amount=max_bond)
required_trades = strategy.calculate_trades(
existing_position=None,
answer=self.get_job_answer(result),
market=self,
)
assert (
len(required_trades) == 1
), f"Shouldn't process same job twice: {required_trades}"
trade = required_trades[0]
assert trade.trade_type == TradeType.BUY, "Should only buy on job markets."
assert trade.outcome, "Should buy only YES on job markets."
assert (
trade.amount.currency == Currency.xDai
Comment on lines +105 to +108
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🛠️ Refactor suggestion

Replace assertions with explicit exception handling

The assertions in get_job_trade check for specific conditions but will raise generic AssertionErrors if they fail. It's better to use explicit exceptions to provide clearer error messages and improve code robustness.

Consider replacing the assertions with exceptions:

if trade.trade_type != TradeType.BUY:
    raise ValueError("Only 'BUY' trade types are supported on job markets.")
if not trade.outcome:
    raise ValueError("Trade outcome must be 'YES' on job markets.")
if trade.amount.currency != Currency.xDai:
    raise ValueError("Only xDai currency is supported for trades.")

), "Should work only on real-money markets."
return required_trades[0]

@staticmethod
def from_omen_market(market: OmenMarket) -> "OmenJobAgentMarket":
return OmenJobAgentMarket.from_omen_agent_market(
Expand Down Expand Up @@ -77,38 +128,3 @@ def from_omen_agent_market(market: OmenAgentMarket) -> "OmenJobAgentMarket":
finalized_time=market.finalized_time,
fees=market.fees,
)


def compute_job_reward(
market: OmenAgentMarket, max_bond: float, web3: Web3 | None = None
) -> float:
# Because jobs are powered by prediction markets, potentional reward depends on job's liquidity and our will to bond (bet) our xDai into our job completion.
strategy = KellyBettingStrategy(max_bet_amount=max_bond)
required_trades = strategy.calculate_trades(
existing_position=None,
# We assume that we finish the job and so the probability of the market happening will be 100%.
answer=ProbabilisticAnswer(p_yes=Probability(1.0), confidence=1.0),
market=market,
)

assert (
len(required_trades) == 1
), f"Shouldn't process same job twice: {required_trades}"
trade = required_trades[0]
assert trade.trade_type == TradeType.BUY, "Should only buy on job markets."
assert trade.outcome, "Should buy only YES on job markets."
assert (
trade.amount.currency == Currency.xDai
), "Should work only on real-money markets."

reward = (
market.get_buy_token_amount(
bet_amount=BetAmount(
amount=trade.amount.amount, currency=trade.amount.currency
),
direction=trade.outcome,
).amount
- trade.amount.amount
)

return reward
12 changes: 12 additions & 0 deletions prediction_market_agent_tooling/markets/markets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,8 @@
from enum import Enum

from prediction_market_agent_tooling.config import APIKeys
from prediction_market_agent_tooling.jobs.jobs_models import JobAgentMarket
from prediction_market_agent_tooling.jobs.omen.omen_jobs import OmenJobAgentMarket
from prediction_market_agent_tooling.markets.agent_market import (
AgentMarket,
FilterBy,
Expand Down Expand Up @@ -46,6 +48,12 @@ def market_class(self) -> type[AgentMarket]:
raise ValueError(f"Unknown market type: {self}")
return MARKET_TYPE_TO_AGENT_MARKET[self]

@property
def job_class(self) -> type[JobAgentMarket]:
if self not in JOB_MARKET_TYPE_TO_JOB_AGENT_MARKET:
raise ValueError(f"Unknown market type: {self}")
return JOB_MARKET_TYPE_TO_JOB_AGENT_MARKET[self]

@property
def is_blockchain_market(self) -> bool:
return self in [MarketType.OMEN, MarketType.POLYMARKET]
Expand All @@ -58,6 +66,10 @@ def is_blockchain_market(self) -> bool:
MarketType.METACULUS: MetaculusAgentMarket,
}

JOB_MARKET_TYPE_TO_JOB_AGENT_MARKET: dict[MarketType, type[JobAgentMarket]] = {
MarketType.OMEN: OmenJobAgentMarket,
}


def get_binary_markets(
limit: int,
Expand Down
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