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# utils/smart_naming.py
from datetime import datetime
import streamlit as st
import time
import json
def generate_chat_name(chat_history, claude_service, max_retries=3, retry_delay=2):
"""Generate a smart name based on chat content with retry logic"""
def extract_basic_name():
"""Extract basic name from content if API fails"""
for entry in chat_history:
if entry.get('analysis'):
# Look for patterns, tickers, or key terms
analysis = entry['analysis'].lower()
# Look for tickers (uppercase words 1-5 chars)
words = analysis.split()
tickers = [word.upper() for word in words
if word.isupper() and 1 <= len(word) <= 5]
# Look for common patterns
patterns = ["bullish", "bearish", "trend", "support", "resistance",
"breakout", "breakdown", "reversal"]
found_patterns = [p for p in patterns if p in analysis]
if tickers and found_patterns:
return f"{tickers[0]} {found_patterns[0].title()} Analysis"
elif tickers:
return f"{tickers[0]} Technical Analysis"
elif found_patterns:
return f"{found_patterns[0].title()} Pattern Analysis"
return None
# First try API with retries
for attempt in range(max_retries):
try:
# Combine all analyses into one text for summarization
full_text = ""
for entry in chat_history:
if entry.get('analysis'):
full_text += entry['analysis'] + "\n"
if not full_text:
return None
prompt = """Based on this trading analysis, create a very short (3-6 words) title that captures the key focus.
Make it specific but concise. Include any relevant tickers or patterns mentioned.
Example formats:
- "AAPL Bullish Breakout Analysis"
- "SPY Multiple Timeframe Support"
- "Crypto Markets Correlation Study"
Analysis text:
{text}
"""
summary = claude_service.generate_educational_content(prompt.format(text=full_text))
if summary:
# Clean up the summary
summary = summary.strip().strip('"').strip("'")
# Add timestamp for uniqueness
timestamp = datetime.now().strftime("%Y%m%d")
return f"{summary}_{timestamp}"
except Exception as e:
if attempt < max_retries - 1: # Don't sleep on last attempt
time.sleep(retry_delay)
continue
# If API fails, try basic name extraction
basic_name = extract_basic_name()
if basic_name:
timestamp = datetime.now().strftime("%Y%m%d")
return f"{basic_name}_{timestamp}"
# Final fallback
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
return f"Trading_Analysis_{timestamp}" |