GetWalletBalance -> GetBalance

prediction_market_agent/agents/microchain_agent/functions.py

@@ -1,4 +1,3 @@
-import pprint
 import typing as t
 from decimal import Decimal
 from typing import cast
@@ -16,10 +15,10 @@
 from prediction_market_agent_tooling.markets.omen.omen_subgraph_handler import (
     OmenSubgraphHandler,
 )
-from prediction_market_agent_tooling.tools.balances import get_balances
 
 from prediction_market_agent.agents.microchain_agent.utils import (
     MicroMarket,
+    get_balance,
     get_binary_market_from_question,
     get_binary_markets,
     get_market_token_balance,
@@ -28,7 +27,6 @@
 )
 from prediction_market_agent.utils import APIKeys
 
-balance = 50
 outcomeTokens = {}
 outcomeTokens["Will Joe Biden get reelected in 2024?"] = {"yes": 0, "no": 0}
 outcomeTokens["Will Bitcoin hit 100k in 2024?"] = {"yes": 0, "no": 0}
@@ -100,21 +98,6 @@ def __call__(self, a: str) -> float:
         return 0.0
 
 
-class GetBalance(MarketFunction):
-    @property
-    def description(self) -> str:
-        return "Use this function to get your own balance in $"
-
-    @property
-    def example_args(self) -> list[str]:
-        return []
-
-    def __call__(self) -> float:
-        print(f"Your balance is: {balance} and ")
-        pprint.pprint(outcomeTokens)
-        return balance
-
-
 class BuyTokens(MarketFunction):
     def __init__(self, market_type: MarketType, outcome: str):
         self.outcome = outcome
@@ -222,25 +205,21 @@ def example_args(self) -> list[str]:
         ]
 
     def __call__(self, summary: str) -> str:
-        # print(summary)
-        # pprint.pprint(outcomeTokens)
         return summary
 
 
-class GetWalletBalance(MarketFunction):
+class GetBalance(MarketFunction):
     @property
     def description(self) -> str:
-        return "Use this function to fetch your balance, given in xDAI units."
+        currency = self.market_type.market_class.currency
+        return f"Use this function to fetch your balance, given in {currency} units."
 
     @property
     def example_args(self) -> list[str]:
         return []
 
     def __call__(self) -> Decimal:
-        # We focus solely on xDAI balance for now to avoid the agent having to wrap/unwrap xDAI.
-        user_address_checksummed = APIKeys().bet_from_address
-        balance = get_balances(user_address_checksummed)
-        return balance.xdai
+        return get_balance(market_type=self.market_type).amount
 
 
 class GetUserPositions(MarketFunction):
@@ -263,7 +242,7 @@ def __call__(self, user_address: str) -> list[OmenUserPosition]:
 MISC_FUNCTIONS = [
     Sum,
     Product,
-    SummarizeLearning,
+    # SummarizeLearning,
 ]
 
 # Functions that interact with the prediction markets
@@ -275,6 +254,5 @@ def __call__(self, user_address: str) -> list[OmenUserPosition]:
     BuyNo,
     SellYes,
     SellNo,
-    GetWalletBalance,
     GetUserPositions,
 ]

prediction_market_agent/agents/microchain_agent/utils.py

@@ -1,9 +1,12 @@
+from decimal import Decimal
+
 from eth_typing import ChecksumAddress
 from prediction_market_agent_tooling.markets.agent_market import (
     AgentMarket,
     FilterBy,
     SortBy,
 )
+from prediction_market_agent_tooling.markets.data_models import BetAmount
 from prediction_market_agent_tooling.markets.markets import MarketType
 from prediction_market_agent_tooling.markets.omen.data_models import (
     OMEN_FALSE_OUTCOME,
@@ -15,10 +18,13 @@
 from prediction_market_agent_tooling.markets.omen.omen_subgraph_handler import (
     OmenSubgraphHandler,
 )
+from prediction_market_agent_tooling.tools.balances import get_balances
 from prediction_market_agent_tooling.tools.hexbytes_custom import HexBytes
 from pydantic import BaseModel
 from web3.types import Wei
 
+from prediction_market_agent.utils import APIKeys
+
 
 class MicroMarket(BaseModel):
     question: str
@@ -50,6 +56,18 @@ def get_binary_markets(market_type: MarketType) -> list[AgentMarket]:
     return markets
 
 
+def get_balance(market_type: MarketType) -> BetAmount:
+    currency = market_type.market_class.currency
+    if market_type == MarketType.OMEN:
+        # We focus solely on xDAI balance for now to avoid the agent having to wrap/unwrap xDAI.
+        return BetAmount(
+            amount=Decimal(get_balances(APIKeys().bet_from_address).xdai),
+            currency=currency,
+        )
+    else:
+        raise ValueError(f"Market type '{market_type}' not supported")
+
+
 def get_binary_market_from_question(
     market: str, market_type: MarketType
 ) -> AgentMarket:

tests/agents/test_microchain.py

@@ -15,9 +15,9 @@
     MISC_FUNCTIONS,
     BuyNo,
     BuyYes,
+    GetBalance,
     GetMarkets,
     GetUserPositions,
-    GetWalletBalance,
 )
 from prediction_market_agent.agents.microchain_agent.utils import (
     get_binary_markets,
@@ -54,7 +54,7 @@ def test_buy_no(market_type: MarketType) -> None:
 
 @pytest.mark.parametrize("market_type", [MarketType.OMEN])
 def test_replicator_has_balance_gt_0(market_type: MarketType) -> None:
-    balance = GetWalletBalance(market_type=market_type)()
+    balance = GetBalance(market_type=market_type)()
     assert balance > 0