Botcamp/ Triple SMA | Concept AI Strategy Builder

hummingbot/client/command/silly_commands.py

@@ -3,6 +3,7 @@
     TYPE_CHECKING,
 )
 from hummingbot.core.utils.async_utils import safe_ensure_future
+from scripts.ai_helper_concept import AiHelperConcept
 
 if TYPE_CHECKING:
     from hummingbot.client.hummingbot_application import HummingbotApplication
@@ -36,6 +37,9 @@ def be_silly(self,  # type: HummingbotApplication
         elif command == "dennis":
             safe_ensure_future(self.silly_dennis())
             return True
+        elif command == "ai":
+            safe_ensure_future(self.proxyAiCommand(raw_command))
+            return True
         else:
             return False
 
@@ -213,3 +217,13 @@ def display_alert(self, custom_alert = None):
             except Exception:
                 pass
         return f"{alert}" + ("\n" * 18)
+
+    async def proxyAiCommand(self, # type: HummingbotApplication
+                             raw_command: str):
+        self.app.log("")
+        self.app.log("thinking...")
+        self.app.log("")
+        self.app.log( "HUMMING AI: " + await AiHelperConcept.command_proxy(raw_command) )
+        self.app.log("")
+
+

hummingbot/strategy/directional_strategy_base.py

@@ -65,6 +65,7 @@ class DirectionalStrategyBase(ScriptStrategyBase):
     time_limit_order_type: OrderType = OrderType.MARKET
     trailing_stop_activation_delta = 0.003
     trailing_stop_trailing_delta = 0.001
+    cooldown_after_execution = 30
 
     # Create the candles that we want to use and the thresholds for the indicators
     candles: List[CandlesBase]
@@ -89,6 +90,15 @@ def is_perpetual(self):
         """
         return "perpetual" in self.exchange
 
+    @property
+    def max_active_executors_condition(self):
+        return len(self.get_active_executors()) < self.max_executors
+
+    @property
+    def time_between_signals_condition(self):
+        seconds_since_last_signal = self.current_timestamp - self.get_timestamp_of_last_executor()
+        return seconds_since_last_signal > self.cooldown_after_execution
+
     def get_csv_path(self) -> str:
         today = datetime.datetime.today()
         csv_path = data_path() + f"/{self.directional_strategy_name}_position_executors_{self.exchange}_{self.trading_pair}_{today.day:02d}-{today.month:02d}-{today.year}.csv"
@@ -119,22 +129,32 @@ def on_stop(self):
         for candle in self.candles:
             candle.stop()
 
-    def get_active_executors(self):
+    def get_active_executors(self) -> List[PositionExecutor]:
         return [signal_executor for signal_executor in self.active_executors
                 if not signal_executor.is_closed]
 
+    def get_closed_executors(self) -> List[PositionExecutor]:
+        return [signal_executor for signal_executor in self.active_executors
+                if signal_executor.is_closed]
+
+    def get_timestamp_of_last_executor(self):
+        if len(self.stored_executors) > 0:
+            return self.stored_executors[-1].close_timestamp
+        else:
+            return 0
+
     def on_tick(self):
+        self.clean_and_store_executors()
         if self.is_perpetual:
             self.check_and_set_leverage()
-        if len(self.get_active_executors()) < self.max_executors and self.all_candles_ready:
+        if self.max_active_executors_condition and self.all_candles_ready and self.time_between_signals_condition:
             position_config = self.get_position_config()
             if position_config:
                 signal_executor = PositionExecutor(
                     strategy=self,
                     position_config=position_config,
                 )
                 self.active_executors.append(signal_executor)
-        self.clean_and_store_executors()
 
     def get_position_config(self):
         signal = self.get_signal()
@@ -287,4 +307,4 @@ def close_open_positions(self):
                              position_action=PositionAction.CLOSE)
 
     def market_data_extra_info(self):
-        return ["\n"]
+        return ["\n"]