#!/usr/bin/env python3
"""Preview DingTalk message format using saved signal"""
import json
import sys

# Add current directory to path
sys.path.insert(0, '/Users/aaron/source_code/tradus-ai/realtime-ingestion')

from notifiers.dingtalk import DingTalkNotifier

# Load the saved signal
with open('/Users/aaron/source_code/tradus-ai/realtime-ingestion/output/latest_signal.json', 'r') as f:
    signal = json.load(f)

# Create DingTalk notifier (without webhook for preview only)
notifier = DingTalkNotifier(webhook_url=None, enabled=False)

# Debug: Check signal structure
print("Signal keys:", list(signal.keys()))

# Format the message
aggregated_signal = signal.get('aggregated_signal', {})
if not aggregated_signal:
    print("ERROR: aggregated_signal is empty!")
    aggregated_signal = signal  # Maybe the whole signal is the aggregated_signal

print("Aggregated signal keys:", list(aggregated_signal.keys()) if aggregated_signal else "None")

try:
    markdown = notifier._format_signal_markdown(aggregated_signal)
except Exception as e:
    print(f"ERROR formatting markdown: {e}")
    import traceback
    traceback.print_exc()
    markdown = "Error formatting message"

print("=" * 80)
print("📱 DINGTALK MESSAGE PREVIEW")
print("=" * 80)
print(markdown)
print("=" * 80)

# Show data structure for debugging
print("\n\n")
print("=" * 80)
print("📊 DATA STRUCTURE DEBUG")
print("=" * 80)

llm_signal = aggregated_signal.get('llm_signal', {})
opportunities = llm_signal.get('opportunities', {})
recommendations = llm_signal.get('recommendations_by_timeframe', {})

print("\nopportunities keys:")
for key in opportunities.keys():
    print(f"  - {key}")

print("\nshort_term_5m_15m_1h:")
short_term = opportunities.get('short_term_5m_15m_1h', {})
print(f"  exists: {short_term.get('exists')}")
print(f"  direction: {short_term.get('direction')}")
print(f"  reasoning: {short_term.get('reasoning', '')[:100]}...")

print("\nmedium_term_4h_1d:")
medium_term = opportunities.get('medium_term_4h_1d', {})
print(f"  exists: {medium_term.get('exists')}")
print(f"  reasoning: {medium_term.get('reasoning', '')[:100]}...")

print("\nrecommendations_by_timeframe:")
print(f"  short_term: {recommendations.get('short_term', '')[:100]}...")
print(f"  medium_term: {recommendations.get('medium_term', '')[:100]}...")
print(f"  long_term: {recommendations.get('long_term', '')[:100]}...")