Files
gogo2/debug/test_orchestrator_predictions.py
Dobromir Popov d0cf04536c fix dash actions
2025-07-04 02:24:18 +03:00

101 lines
3.9 KiB
Python

#!/usr/bin/env python3
"""
Test script to debug orchestrator prediction issues
"""
import sys
import os
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
from core.orchestrator import TradingOrchestrator
from core.data_provider import DataProvider
import asyncio
import logging
# Set up logging
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)
async def test_orchestrator_predictions():
"""Test orchestrator prediction generation"""
logger.info("=" * 60)
logger.info("TESTING ORCHESTRATOR PREDICTIONS")
logger.info("=" * 60)
# Initialize components
logger.info("1. Initializing orchestrator...")
data_provider = DataProvider()
orchestrator = TradingOrchestrator(data_provider)
# Check configuration
logger.info("2. Checking orchestrator configuration...")
logger.info(f" Confidence threshold: {orchestrator.confidence_threshold}")
logger.info(f" Confidence threshold close: {orchestrator.confidence_threshold_close}")
logger.info(f" Model weights: {orchestrator.model_weights}")
# Check registered models
logger.info("3. Checking registered models...")
if hasattr(orchestrator, 'model_registry'):
# Check what methods are available
registry_methods = [method for method in dir(orchestrator.model_registry) if not method.startswith('_')]
logger.info(f" Model registry methods: {registry_methods}")
# Check if we have models
if hasattr(orchestrator, 'rl_agent'):
logger.info(f" RL Agent available: {orchestrator.rl_agent is not None}")
if hasattr(orchestrator, 'cnn_model'):
logger.info(f" CNN Model available: {orchestrator.cnn_model is not None}")
if hasattr(orchestrator, 'extrema_trainer'):
logger.info(f" Extrema Trainer available: {orchestrator.extrema_trainer is not None}")
else:
logger.info(" No model registry found")
# Test prediction generation
logger.info("4. Testing prediction generation...")
symbol = 'ETH/USDT'
try:
# Get all predictions
predictions = await orchestrator._get_all_predictions(symbol)
logger.info(f" Total predictions: {len(predictions)}")
for i, pred in enumerate(predictions):
logger.info(f" Prediction {i+1}: {pred.action} (confidence: {pred.confidence:.3f}, model: {pred.model_name})")
# Test decision making
logger.info("5. Testing decision making...")
for i in range(3): # Test multiple decisions
decision = await orchestrator.make_trading_decision(symbol)
if decision:
logger.info(f" Decision {i+1}: {decision.action} (confidence: {decision.confidence:.3f})")
logger.info(f" Reasoning: {decision.reasoning}")
else:
logger.info(f" Decision {i+1}: None")
# Wait a bit between decisions
await asyncio.sleep(1)
# Test fallback prediction
logger.info("6. Testing fallback prediction...")
current_price = data_provider.get_current_price(symbol)
if current_price:
fallback = await orchestrator._generate_fallback_prediction(symbol, current_price)
if fallback:
logger.info(f" Fallback prediction: {fallback.action} (confidence: {fallback.confidence:.3f})")
else:
logger.info(" No fallback prediction generated")
else:
logger.info(" No current price available for fallback test")
except Exception as e:
logger.error(f" Error testing predictions: {e}")
import traceback
traceback.print_exc()
logger.info("=" * 60)
logger.info("TEST COMPLETE")
logger.info("=" * 60)
if __name__ == "__main__":
asyncio.run(test_orchestrator_predictions())