469 missing information in ipfsagentresult

prediction_market_agent_tooling/deploy/agent.py

@@ -153,10 +153,10 @@ def langfuse_update_current_trace(
             input=input,
             output=output,
             user_id=user_id or getpass.getuser(),
-            session_id=session_id
-            or self.session_id,  # All traces within a single run execution will be grouped under a single session.
-            version=version
-            or APIKeys().LANGFUSE_DEPLOYMENT_VERSION,  # Optionally, mark the current deployment with version (e.g. add git commit hash during docker building).
+            session_id=session_id or self.session_id,
+            # All traces within a single run execution will be grouped under a single session.
+            version=version or APIKeys().LANGFUSE_DEPLOYMENT_VERSION,
+            # Optionally, mark the current deployment with version (e.g. add git commit hash during docker building).
             release=release,
             metadata=metadata,
             tags=tags,
@@ -342,6 +342,10 @@ def update_langfuse_trace_by_processed_market(
             ]
         )
 
+    @property
+    def agent_name(self) -> str:
+        return self.__class__.__name__
+
     def check_min_required_balance_to_operate(self, market_type: MarketType) -> None:
         api_keys = APIKeys()
 
@@ -441,10 +445,13 @@ def after_process_market(
         market_type: MarketType,
         market: AgentMarket,
         processed_market: ProcessedMarket | None,
+        agent_name: str,
     ) -> None:
         keys = APIKeys()
         if self.store_prediction:
-            market.store_prediction(processed_market=processed_market, keys=keys)
+            market.store_prediction(
+                processed_market=processed_market, keys=keys, agent_name=self.agent_name
+            )
         else:
             logger.info(
                 f"Prediction {processed_market} not stored because {self.store_prediction=}."
@@ -472,7 +479,9 @@ def process_markets(self, market_type: MarketType) -> None:
         for market in available_markets:
             self.before_process_market(market_type, market)
             processed_market = self.process_market(market_type, market)
-            self.after_process_market(market_type, market, processed_market)
+            self.after_process_market(
+                market_type, market, processed_market, self.agent_name
+            )
 
             if processed_market is not None:
                 processed += 1
@@ -611,12 +620,15 @@ def after_process_market(
         market_type: MarketType,
         market: AgentMarket,
         processed_market: ProcessedMarket | None,
+        agent_name: str,
     ) -> None:
         api_keys = APIKeys()
-        super().after_process_market(market_type, market, processed_market)
+        super().after_process_market(
+            market_type, market, processed_market, self.agent_name
+        )
         if isinstance(processed_market, ProcessedTradedMarket):
             if self.store_trades:
-                market.store_trades(processed_market, api_keys)
+                market.store_trades(processed_market, api_keys, self.agent_name)
             else:
                 logger.info(
                     f"Trades {processed_market.trades} not stored because {self.store_trades=}."

prediction_market_agent_tooling/markets/agent_market.py

@@ -231,15 +231,21 @@ def verify_operational_balance(api_keys: APIKeys) -> bool:
         raise NotImplementedError("Subclasses must implement this method")
 
     def store_prediction(
-        self, processed_market: ProcessedMarket | None, keys: APIKeys
+        self,
+        processed_market: ProcessedMarket | None,
+        keys: APIKeys,
+        agent_name: str,
     ) -> None:
         """
         If market allows to upload predictions somewhere, implement it in this method.
         """
         raise NotImplementedError("Subclasses must implement this method")
 
     def store_trades(
-        self, traded_market: ProcessedTradedMarket | None, keys: APIKeys
+        self,
+        traded_market: ProcessedTradedMarket | None,
+        keys: APIKeys,
+        agent_name: str,
     ) -> None:
         """
         If market allows to upload trades somewhere, implement it in this method.

prediction_market_agent_tooling/markets/metaculus/metaculus.py

@@ -107,7 +107,7 @@ def get_binary_markets(
         return [MetaculusAgentMarket.from_data_model(q) for q in all_questions[:limit]]
 
     def store_prediction(
-        self, processed_market: ProcessedMarket | None, keys: APIKeys
+        self, processed_market: ProcessedMarket | None, keys: APIKeys, agent_name: str
     ) -> None:
         if processed_market is not None:
             make_prediction(self.id, processed_market.answer.p_yes)

prediction_market_agent_tooling/markets/omen/data_models.py

@@ -798,7 +798,7 @@ def from_tuple(values: tuple[t.Any]) -> "ContractPrediction":
 
 class IPFSAgentResult(BaseModel):
     reasoning: str
-
+    agent_name: str
     model_config = ConfigDict(
         extra="forbid",
     )

prediction_market_agent_tooling/markets/omen/omen.py

@@ -413,17 +413,21 @@ def get_trade_balance(api_keys: APIKeys, web3: Web3 | None = None) -> xDai:
     @staticmethod
     def verify_operational_balance(api_keys: APIKeys) -> bool:
         return get_total_balance(
-            api_keys.public_key,  # Use `public_key`, not `bet_from_address` because transaction costs are paid from the EOA wallet.
+            api_keys.public_key,
+            # Use `public_key`, not `bet_from_address` because transaction costs are paid from the EOA wallet.
             sum_wxdai=False,
         ) > xdai_type(0.001)
 
     def store_prediction(
-        self, processed_market: ProcessedMarket | None, keys: APIKeys
+        self, processed_market: ProcessedMarket | None, keys: APIKeys, agent_name: str
     ) -> None:
         """On Omen, we have to store predictions along with trades, see `store_trades`."""
 
     def store_trades(
-        self, traded_market: ProcessedTradedMarket | None, keys: APIKeys
+        self,
+        traded_market: ProcessedTradedMarket | None,
+        keys: APIKeys,
+        agent_name: str,
     ) -> None:
         if traded_market is None:
             logger.warning(f"No prediction for market {self.id}, not storing anything.")
@@ -437,7 +441,7 @@ def store_trades(
         if keys.enable_ipfs_upload:
             logger.info("Storing prediction on IPFS.")
             ipfs_hash = IPFSHandler(keys).store_agent_result(
-                IPFSAgentResult(reasoning=reasoning)
+                IPFSAgentResult(reasoning=reasoning, agent_name=agent_name)
             )
             ipfs_hash_decoded = ipfscidv0_to_byte32(ipfs_hash)
 
@@ -1237,12 +1241,12 @@ def redeem_from_all_user_positions(
 
         if not conditional_token_contract.is_condition_resolved(condition_id):
             logger.info(
-                f"[{index+1} / {len(user_positions)}] Skipping redeem, {user_position.id=} isn't resolved yet."
+                f"[{index + 1} / {len(user_positions)}] Skipping redeem, {user_position.id=} isn't resolved yet."
             )
             continue
 
         logger.info(
-            f"[{index+1} / {len(user_positions)}] Processing redeem from {user_position.id=}."
+            f"[{index + 1} / {len(user_positions)}] Processing redeem from {user_position.id=}."
         )
 
         original_balances = get_balances(public_key, web3)
@@ -1263,9 +1267,11 @@ def redeem_from_all_user_positions(
 def get_binary_market_p_yes_history(market: OmenAgentMarket) -> list[Probability]:
     history: list[Probability] = []
     trades = sorted(
-        OmenSubgraphHandler().get_trades(  # We need to look at price both after buying or selling, so get trades, not bets.
+        OmenSubgraphHandler().get_trades(
+            # We need to look at price both after buying or selling, so get trades, not bets.
             market_id=market.market_maker_contract_address_checksummed,
-            end_time=market.close_time,  # Even after market is closed, there can be many `Sell` trades which will converge the probability to the true one.
+            end_time=market.close_time,
+            # Even after market is closed, there can be many `Sell` trades which will converge the probability to the true one.
         ),
         key=lambda x: x.creation_datetime,
     )