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7 Commits

Author SHA1 Message Date
shokollm
ad6e57655d fix: correct import paths in ai_agent module
- Fix relative import path in crew.py (from ..core to ...core)
- Update __init__.py exports to match actual class names
- Remove incorrect CrewAgent and LLMConnector exports
2026-04-09 15:27:09 +00:00
ac5e9d8b81 Merge pull request 'fix: add error logging to simulate engine to prevent silent failures' (#38) from fix/issue-30 into main 2026-04-09 12:19:36 +02:00
shokollm
81f3342365 fix: add error logging to simulate engine to prevent silent failures
Errors during price fetching are now logged and stored in an errors list,
allowing users to see error count/warnings in simulation results.

Acceptance Criteria:
- [x] Errors are logged (not silently swallowed)
- [x] User can see error count/warnings in simulation results
- [x] Simulation completes even if some price fetches fail (graceful degradation)
2026-04-09 10:16:22 +00:00
6adad0701d Merge pull request 'fix: consolidate AveCloudClient to single implementation' (#37) from fix/issue-29 into main 2026-04-09 12:11:59 +02:00
shokollm
405b35c3ba fix: consolidate AveCloudClient to single implementation in services/ave/client.py 2026-04-09 10:06:16 +00:00
dd25d38e7e Merge pull request 'feat: implement stop-loss and take-profit risk management' (#36) from fix/issue-28 into main 2026-04-09 11:39:50 +02:00
shokollm
da8327c0e0 feat: implement stop-loss and take-profit in backtest and simulate engines 2026-04-09 09:14:08 +00:00
6 changed files with 205 additions and 90 deletions

View File

@@ -1,4 +1,4 @@
from .crew import CrewAgent from .crew import TradingCrew, get_trading_crew
from .llm_connector import LLMConnector from .llm_connector import MiniMaxLLM, MiniMaxConnector
__all__ = ["CrewAgent", "LLMConnector"] __all__ = ["TradingCrew", "get_trading_crew", "MiniMaxLLM", "MiniMaxConnector"]

View File

@@ -1,7 +1,7 @@
from typing import List, Optional, Dict, Any from typing import List, Optional, Dict, Any
from crewai import Agent, Task, Crew from crewai import Agent, Task, Crew
from .llm_connector import MiniMaxConnector, MiniMaxLLM from .llm_connector import MiniMaxConnector, MiniMaxLLM
from ..core.config import get_settings from ...core.config import get_settings
class StrategyValidator: class StrategyValidator:

View File

@@ -90,6 +90,22 @@ class AveCloudClient:
return data.get("data", []) return data.get("data", [])
raise Exception(f"Failed to fetch klines: {data}") raise Exception(f"Failed to fetch klines: {data}")
async def get_token_price(self, token_id: str) -> Optional[Dict[str, Any]]:
url = f"{self.DATA_API_URL}/v2/tokens/price"
async with httpx.AsyncClient() as client:
response = await client.post(
url,
headers=self._data_headers(),
json={"token_ids": [token_id]},
timeout=30.0,
)
response.raise_for_status()
data = response.json()
if data.get("status") == 200:
prices = data.get("data", {})
return prices.get(token_id)
return None
async def get_trending_tokens( async def get_trending_tokens(
self, chain: Optional[str] = None, limit: int = 20 self, chain: Optional[str] = None, limit: int = 20
) -> List[Dict[str, Any]]: ) -> List[Dict[str, Any]]:

View File

@@ -1,70 +0,0 @@
import httpx
from typing import List, Dict, Any, Optional
from datetime import datetime
class AveCloudClient:
BASE_URL = "https://prod.ave-api.com"
def __init__(self, api_key: str, plan: str = "free"):
self.api_key = api_key
self.plan = plan
def _headers(self) -> Dict[str, str]:
return {"X-API-KEY": self.api_key}
async def get_klines(
self,
token_id: str,
interval: str = "1h",
limit: int = 100,
start_time: Optional[int] = None,
end_time: Optional[int] = None,
) -> List[Dict[str, Any]]:
url = f"{self.BASE_URL}/v2/klines/token/{token_id}"
params = {"interval": interval, "limit": limit}
if start_time:
params["start_time"] = start_time
if end_time:
params["end_time"] = end_time
async with httpx.AsyncClient() as client:
response = await client.get(
url, headers=self._headers(), params=params, timeout=30.0
)
response.raise_for_status()
data = response.json()
if data.get("status") == 200:
return data.get("data", [])
raise Exception(f"Failed to fetch klines: {data}")
async def get_token_price(self, token_id: str) -> Optional[Dict[str, Any]]:
url = f"{self.BASE_URL}/v2/tokens/price"
async with httpx.AsyncClient() as client:
response = await client.post(
url,
headers=self._headers(),
json={"token_ids": [token_id]},
timeout=30.0,
)
response.raise_for_status()
data = response.json()
if data.get("status") == 200:
prices = data.get("data", {})
return prices.get(token_id)
return None
async def get_batch_prices(self, token_ids: List[str]) -> Dict[str, Dict[str, Any]]:
url = f"{self.BASE_URL}/v2/tokens/price"
async with httpx.AsyncClient() as client:
response = await client.post(
url,
headers=self._headers(),
json={"token_ids": token_ids},
timeout=30.0,
)
response.raise_for_status()
data = response.json()
if data.get("status") == 200:
return data.get("data", {})
return {}

View File

@@ -2,7 +2,7 @@ import uuid
import asyncio import asyncio
from datetime import datetime from datetime import datetime
from typing import Dict, Any, List, Optional from typing import Dict, Any, List, Optional
from .ave_client import AveCloudClient from ..ave.client import AveCloudClient
class BacktestEngine: class BacktestEngine:
@@ -20,10 +20,15 @@ class BacktestEngine:
self.strategy_config = config.get("strategy_config", {}) self.strategy_config = config.get("strategy_config", {})
self.conditions = self.strategy_config.get("conditions", []) self.conditions = self.strategy_config.get("conditions", [])
self.actions = self.strategy_config.get("actions", []) self.actions = self.strategy_config.get("actions", [])
self.risk_management = self.strategy_config.get("risk_management", {})
self.stop_loss_percent = self.risk_management.get("stop_loss_percent")
self.take_profit_percent = self.risk_management.get("take_profit_percent")
self.initial_balance = config.get("initial_balance", 10000.0) self.initial_balance = config.get("initial_balance", 10000.0)
self.current_balance = self.initial_balance self.current_balance = self.initial_balance
self.position = 0.0 self.position = 0.0
self.position_token = "" self.position_token = ""
self.entry_price: Optional[float] = None
self.entry_time: Optional[int] = None
self.trades: List[Dict[str, Any]] = [] self.trades: List[Dict[str, Any]] = []
self.running = False self.running = False
@@ -103,11 +108,73 @@ class BacktestEngine:
timestamp = kline.get("timestamp", 0) timestamp = kline.get("timestamp", 0)
if self.position > 0 and self.entry_price is not None:
exit_info = self._check_risk_management(price, timestamp)
if exit_info:
await self._execute_risk_exit(price, timestamp, exit_info)
continue
for condition in self.conditions: for condition in self.conditions:
if self._check_condition(condition, klines, i, price): if self._check_condition(condition, klines, i, price):
await self._execute_actions(price, timestamp, condition) await self._execute_actions(price, timestamp, condition)
break break
def _check_risk_management(
self, current_price: float, timestamp: int
) -> Optional[Dict[str, Any]]:
if self.position <= 0 or self.entry_price is None:
return None
if self.stop_loss_percent is not None:
stop_loss_price = self.entry_price * (1 - self.stop_loss_percent / 100)
if current_price <= stop_loss_price:
return {"reason": "stop_loss", "price": stop_loss_price}
if self.take_profit_percent is not None:
take_profit_price = self.entry_price * (1 + self.take_profit_percent / 100)
if current_price >= take_profit_price:
return {"reason": "take_profit", "price": take_profit_price}
return None
async def _execute_risk_exit(
self, price: float, timestamp: int, exit_info: Dict[str, Any]
):
if self.position <= 0:
return
reason = exit_info["reason"]
sell_amount = self.position * price
self.current_balance += sell_amount
self.trades.append(
{
"type": "sell",
"token": self.position_token,
"price": price,
"amount": sell_amount,
"quantity": self.position,
"timestamp": timestamp,
"exit_reason": reason,
}
)
self.signals.append(
{
"id": str(uuid.uuid4()),
"bot_id": self.bot_id,
"run_id": self.run_id,
"signal_type": "sell",
"token": self.position_token,
"price": price,
"confidence": 1.0,
"reasoning": f"Risk management triggered {reason}",
"executed": False,
"created_at": datetime.utcnow(),
}
)
self.position = 0
self.entry_price = None
self.entry_time = None
def _check_condition( def _check_condition(
self, self,
condition: Dict[str, Any], condition: Dict[str, Any],
@@ -173,6 +240,8 @@ class BacktestEngine:
self.position += amount / price self.position += amount / price
self.current_balance -= amount self.current_balance -= amount
self.position_token = token self.position_token = token
self.entry_price = price
self.entry_time = timestamp
self.trades.append( self.trades.append(
{ {
"type": "buy", "type": "buy",
@@ -209,9 +278,12 @@ class BacktestEngine:
"amount": sell_amount, "amount": sell_amount,
"quantity": self.position, "quantity": self.position,
"timestamp": timestamp, "timestamp": timestamp,
"exit_reason": "manual",
} }
) )
self.position = 0 self.position = 0
self.entry_price = None
self.entry_time = None
self.signals.append( self.signals.append(
{ {
"id": str(uuid.uuid4()), "id": str(uuid.uuid4()),

View File

@@ -1,8 +1,11 @@
import uuid import uuid
import asyncio import asyncio
import logging
from datetime import datetime from datetime import datetime
from typing import Dict, Any, List, Optional from typing import Dict, Any, List, Optional
from ..backtest.ave_client import AveCloudClient from ..ave.client import AveCloudClient
logger = logging.getLogger(__name__)
class SimulateEngine: class SimulateEngine:
@@ -20,6 +23,9 @@ class SimulateEngine:
self.strategy_config = config.get("strategy_config", {}) self.strategy_config = config.get("strategy_config", {})
self.conditions = self.strategy_config.get("conditions", []) self.conditions = self.strategy_config.get("conditions", [])
self.actions = self.strategy_config.get("actions", []) self.actions = self.strategy_config.get("actions", [])
self.risk_management = self.strategy_config.get("risk_management", {})
self.stop_loss_percent = self.risk_management.get("stop_loss_percent")
self.take_profit_percent = self.risk_management.get("take_profit_percent")
self.check_interval = config.get("check_interval", 60) self.check_interval = config.get("check_interval", 60)
self.duration_seconds = config.get("duration_seconds", 3600) self.duration_seconds = config.get("duration_seconds", 3600)
self.auto_execute = config.get("auto_execute", False) self.auto_execute = config.get("auto_execute", False)
@@ -29,6 +35,13 @@ class SimulateEngine:
self.started_at: Optional[datetime] = None self.started_at: Optional[datetime] = None
self.last_price: Optional[float] = None self.last_price: Optional[float] = None
self.last_volume: Optional[float] = None self.last_volume: Optional[float] = None
self.position: float = 0.0
self.position_token: str = ""
self.entry_price: Optional[float] = None
self.entry_time: Optional[int] = None
self.current_balance: float = config.get("initial_balance", 10000.0)
self.trades: List[Dict[str, Any]] = []
self.errors: List[str] = []
async def run(self) -> Dict[str, Any]: async def run(self) -> Dict[str, Any]:
self.running = True self.running = True
@@ -65,7 +78,9 @@ class SimulateEngine:
self.last_volume = current_volume self.last_volume = current_volume
except Exception as e: except Exception as e:
pass logger.warning(f"Failed to get price for {token_id}: {e}")
self.errors.append(f"Price fetch failed for {token_id}: {str(e)}")
continue
for _ in range(self.check_interval): for _ in range(self.check_interval):
if not self.running: if not self.running:
@@ -83,6 +98,8 @@ class SimulateEngine:
self.results = self.results or {} self.results = self.results or {}
self.results["total_signals"] = len(self.signals) self.results["total_signals"] = len(self.signals)
self.results["total_errors"] = len(self.errors)
self.results["errors"] = self.errors
self.results["signals"] = self.signals self.results["signals"] = self.signals
self.results["started_at"] = self.started_at self.results["started_at"] = self.started_at
self.results["ended_at"] = datetime.utcnow() self.results["ended_at"] = datetime.utcnow()
@@ -94,11 +111,70 @@ class SimulateEngine:
): ):
timestamp = int(datetime.utcnow().timestamp() * 1000) timestamp = int(datetime.utcnow().timestamp() * 1000)
if self.position > 0 and self.entry_price is not None:
exit_info = self._check_risk_management(current_price, timestamp)
if exit_info:
await self._execute_risk_exit(current_price, timestamp, exit_info)
return
for condition in self.conditions: for condition in self.conditions:
if self._check_condition(condition, current_price, current_volume): if self._check_condition(condition, current_price, current_volume):
await self._execute_actions(current_price, timestamp, condition) await self._execute_actions(current_price, timestamp, condition)
break break
def _check_risk_management(
self, current_price: float, timestamp: int
) -> Optional[Dict[str, Any]]:
if self.position <= 0 or self.entry_price is None:
return None
if self.stop_loss_percent is not None:
stop_loss_price = self.entry_price * (1 - self.stop_loss_percent / 100)
if current_price <= stop_loss_price:
return {"reason": "stop_loss", "price": stop_loss_price}
if self.take_profit_percent is not None:
take_profit_price = self.entry_price * (1 + self.take_profit_percent / 100)
if current_price >= take_profit_price:
return {"reason": "take_profit", "price": take_profit_price}
return None
async def _execute_risk_exit(
self, price: float, timestamp: int, exit_info: Dict[str, Any]
):
if self.position <= 0:
return
reason = exit_info["reason"]
self.trades.append(
{
"type": "sell",
"token": self.position_token,
"price": price,
"quantity": self.position,
"timestamp": timestamp,
"exit_reason": reason,
}
)
self.signals.append(
{
"id": str(uuid.uuid4()),
"bot_id": self.bot_id,
"run_id": self.run_id,
"signal_type": "sell",
"token": self.position_token,
"price": price,
"confidence": 1.0,
"reasoning": f"Risk management triggered {reason}",
"executed": self.auto_execute,
"created_at": datetime.utcnow(),
}
)
self.position = 0
self.entry_price = None
self.entry_time = None
def _check_condition( def _check_condition(
self, self,
condition: Dict[str, Any], condition: Dict[str, Any],
@@ -146,11 +222,32 @@ class SimulateEngine:
token = matched_condition.get("token", self.token) token = matched_condition.get("token", self.token)
reasoning = f"Condition {matched_condition.get('type')} triggered" reasoning = f"Condition {matched_condition.get('type')} triggered"
for action in self.actions:
action_type = action.get("type", "")
if action_type == "buy":
amount_percent = action.get("amount_percent", 10)
amount = self.current_balance * (amount_percent / 100)
self.position += amount / price
self.position_token = token
self.entry_price = price
self.entry_time = timestamp
self.current_balance -= amount
self.trades.append(
{
"type": "buy",
"token": token,
"price": price,
"amount": amount,
"quantity": amount / price,
"timestamp": timestamp,
}
)
signal = { signal = {
"id": str(uuid.uuid4()), "id": str(uuid.uuid4()),
"bot_id": self.bot_id, "bot_id": self.bot_id,
"run_id": self.run_id, "run_id": self.run_id,
"signal_type": "signal", "signal_type": action_type,
"token": token, "token": token,
"price": price, "price": price,
"confidence": 0.8, "confidence": 0.8,