Address Gemini review: date filtering, caching, dedup, naming + add technicals & competitors
Fixes all 9 Gemini issues: - HIGH: get_news/get_global_news now pass start_date/end_date to API - HIGH: get_sec_filings (renamed from get_insider_transactions) has caching - MEDIUM: Replaced _get2 duplicate with shared _safe_get at module level - MEDIUM: _safe_get returns default instead of None (no more 'None' in strings) - MEDIUM: balance_sheet/cashflow/income_statement now cache formatted results - MEDIUM: String concatenation replaced with list join pattern throughout - MEDIUM: _days_to_range helper eliminates range calculation duplication - MEDIUM: Fallback for unknown indicator types formats dict keys as CSV New Polaris-exclusive methods: - get_technicals: 20 indicators + buy/sell signal in one call - get_competitors: same-sector peers with live price, RSI, sentiment
This commit is contained in:
John Weston
parent
4abad33e0f
commit
b622630e53
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@ -36,6 +36,8 @@ from .polaris import (
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get_sentiment_score as get_polaris_sentiment_score,
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get_sector_analysis as get_polaris_sector_analysis,
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get_news_impact as get_polaris_news_impact,
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get_technicals as get_polaris_technicals,
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get_competitors as get_polaris_competitors,
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)
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# Configuration and routing logic
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@ -149,6 +151,12 @@ VENDOR_METHODS = {
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"get_news_impact": {
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"polaris": get_polaris_news_impact,
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},
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"get_technicals": {
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"polaris": get_polaris_technicals,
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},
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"get_competitors": {
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"polaris": get_polaris_competitors,
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},
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}
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def get_category_for_method(method: str) -> str:
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@ -70,12 +70,41 @@ def _cached(key: str):
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return _cache.get(key)
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def _set_cache(key: str, data: str):
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def _set_cache(key: str, data):
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"""Store data in cache (thread-safe)."""
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with _cache_lock:
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_cache[key] = data
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# ---------------------------------------------------------------------------
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# Shared helpers
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# ---------------------------------------------------------------------------
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def _safe_get(obj, key, default='N/A'):
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"""Get attribute from dict or object, returning default if missing or None."""
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if isinstance(obj, dict):
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val = obj.get(key, default)
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return default if val is None else val
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val = getattr(obj, key, default)
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return default if val is None else val
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def _days_to_range(days: int) -> str:
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"""Convert a day count to a Polaris range string."""
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if days <= 30:
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return "1mo"
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elif days <= 90:
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return "3mo"
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elif days <= 180:
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return "6mo"
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elif days <= 365:
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return "1y"
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elif days <= 730:
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return "2y"
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else:
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return "5y"
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# ---------------------------------------------------------------------------
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# Core Stock APIs
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# ---------------------------------------------------------------------------
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@ -93,23 +122,10 @@ def get_stock_data(
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client = _get_client()
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# Determine range from date span
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start = datetime.strptime(start_date, "%Y-%m-%d")
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end = datetime.strptime(end_date, "%Y-%m-%d")
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days = (end - start).days
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if days <= 30:
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range_param = "1mo"
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elif days <= 90:
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range_param = "3mo"
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elif days <= 180:
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range_param = "6mo"
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elif days <= 365:
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range_param = "1y"
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elif days <= 730:
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range_param = "2y"
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else:
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range_param = "5y"
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range_param = _days_to_range(days)
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try:
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data = client.candles(symbol, interval="1d", range=range_param)
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@ -123,16 +139,19 @@ def get_stock_data(
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# Filter to requested date range
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candles = [c for c in candles if start_date <= c["date"] <= end_date]
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# Format as CSV (matching yfinance output format)
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header = f"# Stock data for {symbol.upper()} from {start_date} to {end_date}\n"
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header += f"# Source: Polaris Knowledge API (multi-provider: Yahoo/TwelveData/FMP)\n"
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header += f"# Total records: {len(candles)}\n\n"
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lines = [
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f"# Stock data for {symbol.upper()} from {start_date} to {end_date}",
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f"# Source: Polaris Knowledge API (multi-provider: Yahoo/TwelveData/FMP)",
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f"# Total records: {len(candles)}",
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"",
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"Date,Open,High,Low,Close,Volume",
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]
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lines.extend(
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f"{c['date']},{c['open']},{c['high']},{c['low']},{c['close']},{c['volume']}"
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for c in candles
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)
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csv = "Date,Open,High,Low,Close,Volume\n"
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for c in candles:
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csv += f"{c['date']},{c['open']},{c['high']},{c['low']},{c['close']},{c['volume']}\n"
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result = header + csv
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result = "\n".join(lines) + "\n"
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_set_cache(cache_key, result)
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return result
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@ -169,23 +188,17 @@ def get_indicators(
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}
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polaris_type = indicator_map.get(indicator.lower(), indicator.lower())
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range_param = _days_to_range(look_back_days)
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# Determine range
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if look_back_days <= 30:
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range_param = "1mo"
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elif look_back_days <= 90:
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range_param = "3mo"
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elif look_back_days <= 180:
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range_param = "6mo"
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else:
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range_param = "1y"
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known_types = {
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"sma", "ema", "rsi", "macd", "bollinger", "atr",
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"stochastic", "adx", "obv", "vwap", "williams_r",
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"cci", "mfi", "roc", "ppo", "trix", "donchian",
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"parabolic_sar", "ichimoku", "fibonacci",
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}
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# Try specific indicator first, fall back to full technicals
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try:
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if polaris_type in ["sma", "ema", "rsi", "macd", "bollinger", "atr",
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"stochastic", "adx", "obv", "vwap", "williams_r",
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"cci", "mfi", "roc", "ppo", "trix", "donchian",
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"parabolic_sar", "ichimoku", "fibonacci"]:
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if polaris_type in known_types:
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data = client.indicators(symbol, type=polaris_type, range=range_param)
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else:
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data = client.technicals(symbol, range=range_param)
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@ -194,38 +207,39 @@ def get_indicators(
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values = data.get("values", [])
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header = f"# Technical Indicator: {indicator} for {symbol.upper()}\n"
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header += f"# Source: Polaris Knowledge API\n"
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header += f"# Period: {range_param} | Data points: {len(values)}\n\n"
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lines = [
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f"# Technical Indicator: {indicator} for {symbol.upper()}",
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f"# Source: Polaris Knowledge API",
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f"# Period: {range_param} | Data points: {len(values) if isinstance(values, list) else 'N/A'}",
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"",
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]
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if isinstance(values, list) and values:
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# Format based on indicator type
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first = values[0]
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if "value" in first:
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csv = "Date,Value\n"
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for v in values:
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csv += f"{v['date']},{v['value']}\n"
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lines.append("Date,Value")
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lines.extend(f"{v['date']},{v.get('value', '')}" for v in values)
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elif "macd" in first:
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csv = "Date,MACD,Signal,Histogram\n"
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for v in values:
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csv += f"{v['date']},{v.get('macd','')},{v.get('signal','')},{v.get('histogram','')}\n"
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lines.append("Date,MACD,Signal,Histogram")
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lines.extend(f"{v['date']},{v.get('macd', '')},{v.get('signal', '')},{v.get('histogram', '')}" for v in values)
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elif "upper" in first:
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csv = "Date,Upper,Middle,Lower\n"
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for v in values:
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csv += f"{v['date']},{v.get('upper','')},{v.get('middle','')},{v.get('lower','')}\n"
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lines.append("Date,Upper,Middle,Lower")
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lines.extend(f"{v['date']},{v.get('upper', '')},{v.get('middle', '')},{v.get('lower', '')}" for v in values)
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elif "k" in first:
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csv = "Date,K,D\n"
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for v in values:
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csv += f"{v['date']},{v.get('k','')},{v.get('d','')}\n"
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lines.append("Date,K,D")
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lines.extend(f"{v['date']},{v.get('k', '')},{v.get('d', '')}" for v in values)
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else:
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csv = str(values)
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# Format dict keys as CSV columns
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keys = list(first.keys())
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lines.append(",".join(keys))
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lines.extend(",".join(str(v.get(k, '')) for k in keys) for v in values)
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elif isinstance(values, dict):
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# Fibonacci or similar
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csv = str(values)
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for k, v in values.items():
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lines.append(f"{k}: {v}")
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else:
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csv = "No indicator data available"
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lines.append("No indicator data available")
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result = header + csv
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result = "\n".join(lines) + "\n"
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_set_cache(cache_key, result)
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return result
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@ -260,23 +274,27 @@ def get_fundamentals(
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except Exception as e:
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return f"Error fetching fundamentals for {symbol}: {e}"
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result = f"# Company Fundamentals: {data.get('company_name', symbol)}\n"
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result += f"# Source: Polaris Knowledge API\n\n"
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result += f"Sector: {data.get('sector', 'N/A')}\n"
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result += f"Industry: {data.get('industry', 'N/A')}\n"
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result += f"Market Cap: {data.get('market_cap_formatted', 'N/A')}\n"
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result += f"P/E Ratio: {data.get('pe_ratio', 'N/A')}\n"
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result += f"Forward P/E: {data.get('forward_pe', 'N/A')}\n"
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result += f"EPS: {data.get('eps', 'N/A')}\n"
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result += f"Revenue: {data.get('revenue_formatted', 'N/A')}\n"
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result += f"EBITDA: {data.get('ebitda_formatted', 'N/A')}\n"
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result += f"Profit Margin: {data.get('profit_margin', 'N/A')}\n"
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result += f"Debt/Equity: {data.get('debt_to_equity', 'N/A')}\n"
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result += f"ROE: {data.get('return_on_equity', 'N/A')}\n"
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result += f"Beta: {data.get('beta', 'N/A')}\n"
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result += f"52-Week High: {data.get('fifty_two_week_high', 'N/A')}\n"
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result += f"52-Week Low: {data.get('fifty_two_week_low', 'N/A')}\n"
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lines = [
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f"# Company Fundamentals: {data.get('company_name', symbol)}",
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f"# Source: Polaris Knowledge API",
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"",
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f"Sector: {_safe_get(data, 'sector')}",
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f"Industry: {_safe_get(data, 'industry')}",
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f"Market Cap: {_safe_get(data, 'market_cap_formatted')}",
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f"P/E Ratio: {_safe_get(data, 'pe_ratio')}",
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f"Forward P/E: {_safe_get(data, 'forward_pe')}",
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f"EPS: {_safe_get(data, 'eps')}",
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f"Revenue: {_safe_get(data, 'revenue_formatted')}",
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f"EBITDA: {_safe_get(data, 'ebitda_formatted')}",
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f"Profit Margin: {_safe_get(data, 'profit_margin')}",
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f"Debt/Equity: {_safe_get(data, 'debt_to_equity')}",
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f"ROE: {_safe_get(data, 'return_on_equity')}",
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f"Beta: {_safe_get(data, 'beta')}",
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f"52-Week High: {_safe_get(data, 'fifty_two_week_high')}",
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f"52-Week Low: {_safe_get(data, 'fifty_two_week_low')}",
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]
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result = "\n".join(lines) + "\n"
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_set_cache(cache_key, result)
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return result
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@ -285,17 +303,27 @@ def get_balance_sheet(
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symbol: Annotated[str, "ticker symbol of the company"],
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) -> str:
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"""Fetch balance sheet from Polaris."""
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cache_key = f"balance_sheet:{symbol}"
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cached = _cached(cache_key)
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if cached:
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return cached
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try:
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data = _get_financials_cached(symbol)
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except Exception as e:
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return f"Error fetching balance sheet for {symbol}: {e}"
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sheets = data.get("balance_sheets", [])
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result = f"# Balance Sheet: {symbol.upper()}\n# Source: Polaris Knowledge API\n\n"
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result += "Date,Total Assets,Total Liabilities,Total Equity\n"
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for s in sheets:
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result += f"{s['date']},{s['total_assets']},{s['total_liabilities']},{s['total_equity']}\n"
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lines = [
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f"# Balance Sheet: {symbol.upper()}",
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f"# Source: Polaris Knowledge API",
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"",
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"Date,Total Assets,Total Liabilities,Total Equity",
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]
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lines.extend(f"{s['date']},{s['total_assets']},{s['total_liabilities']},{s['total_equity']}" for s in sheets)
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result = "\n".join(lines) + "\n"
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_set_cache(cache_key, result)
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return result
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@ -303,13 +331,25 @@ def get_cashflow(
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symbol: Annotated[str, "ticker symbol of the company"],
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) -> str:
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"""Fetch cash flow data from Polaris."""
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cache_key = f"cashflow:{symbol}"
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cached = _cached(cache_key)
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if cached:
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return cached
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try:
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data = _get_financials_cached(symbol)
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except Exception as e:
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return f"Error fetching cashflow for {symbol}: {e}"
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result = f"# Cash Flow: {symbol.upper()}\n# Source: Polaris Knowledge API\n\n"
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result += f"Free Cash Flow: {data.get('free_cash_flow', 'N/A')}\n"
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lines = [
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f"# Cash Flow: {symbol.upper()}",
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f"# Source: Polaris Knowledge API",
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"",
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f"Free Cash Flow: {_safe_get(data, 'free_cash_flow')}",
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]
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result = "\n".join(lines) + "\n"
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_set_cache(cache_key, result)
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return result
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@ -317,17 +357,27 @@ def get_income_statement(
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symbol: Annotated[str, "ticker symbol of the company"],
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) -> str:
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"""Fetch income statement from Polaris."""
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cache_key = f"income_stmt:{symbol}"
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cached = _cached(cache_key)
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if cached:
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return cached
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try:
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data = _get_financials_cached(symbol)
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except Exception as e:
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return f"Error fetching income statement for {symbol}: {e}"
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stmts = data.get("income_statements", [])
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result = f"# Income Statement: {symbol.upper()}\n# Source: Polaris Knowledge API\n\n"
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result += "Date,Revenue,Net Income,Gross Profit\n"
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for s in stmts:
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result += f"{s['date']},{s['revenue']},{s['net_income']},{s['gross_profit']}\n"
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lines = [
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f"# Income Statement: {symbol.upper()}",
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f"# Source: Polaris Knowledge API",
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"",
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"Date,Revenue,Net Income,Gross Profit",
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]
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lines.extend(f"{s['date']},{s['revenue']},{s['net_income']},{s['gross_profit']}" for s in stmts)
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result = "\n".join(lines) + "\n"
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_set_cache(cache_key, result)
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return result
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@ -355,8 +405,7 @@ def get_news(
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client = _get_client()
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try:
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data = client.search(symbol, per_page=20)
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# Handle both dict and typed response objects
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data = client.search(symbol, per_page=20, from_date=start_date, to_date=end_date)
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if hasattr(data, '__dict__') and not isinstance(data, dict):
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data = data.__dict__ if hasattr(data, '__dict__') else {}
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if isinstance(data, dict):
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@ -366,45 +415,45 @@ def get_news(
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except Exception as e:
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return f"Error fetching news for {symbol}: {e}"
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if not briefs:
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return f"No intelligence briefs found for {symbol}"
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return f"No intelligence briefs found for {symbol} between {start_date} and {end_date}"
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result = f"# Intelligence Briefs for {symbol.upper()}\n"
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result += f"# Source: Polaris Knowledge API (sentiment-scored, bias-analyzed)\n"
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result += f"# Total: {len(briefs)} briefs\n\n"
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def _get(obj, key, default='N/A'):
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"""Get attribute from dict or object."""
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if isinstance(obj, dict):
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return obj.get(key, default)
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return getattr(obj, key, default)
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lines = [
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f"# Intelligence Briefs for {symbol.upper()} ({start_date} to {end_date})",
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f"# Source: Polaris Knowledge API (sentiment-scored, bias-analyzed)",
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f"# Total: {len(briefs)} briefs",
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"",
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]
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for b in briefs:
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prov = _get(b, "provenance", {})
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result += f"--- Brief: {_get(b, 'id', '')} ---\n"
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result += f"Date: {_get(b, 'published_at', '')}\n"
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result += f"Headline: {_get(b, 'headline', '')}\n"
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result += f"Summary: {_get(b, 'summary', '')}\n"
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result += f"Category: {_get(b, 'category', '')}\n"
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result += f"Confidence: {_get(prov, 'confidence_score', 'N/A')}\n"
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result += f"Bias Score: {_get(prov, 'bias_score', 'N/A')}\n"
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result += f"Review Status: {_get(prov, 'review_status', 'N/A')}\n"
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result += f"Sentiment: {_get(b, 'sentiment', 'N/A')}\n"
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result += f"Impact Score: {_get(b, 'impact_score', 'N/A')}\n"
|
||||
prov = _safe_get(b, "provenance", {})
|
||||
if not isinstance(prov, dict):
|
||||
prov = {}
|
||||
lines.append(f"--- Brief: {_safe_get(b, 'id', '')} ---")
|
||||
lines.append(f"Date: {_safe_get(b, 'published_at', '')}")
|
||||
lines.append(f"Headline: {_safe_get(b, 'headline', '')}")
|
||||
lines.append(f"Summary: {_safe_get(b, 'summary', '')}")
|
||||
lines.append(f"Category: {_safe_get(b, 'category', '')}")
|
||||
lines.append(f"Confidence: {_safe_get(prov, 'confidence_score')}")
|
||||
lines.append(f"Bias Score: {_safe_get(prov, 'bias_score')}")
|
||||
lines.append(f"Review Status: {_safe_get(prov, 'review_status')}")
|
||||
lines.append(f"Sentiment: {_safe_get(b, 'sentiment')}")
|
||||
lines.append(f"Impact Score: {_safe_get(b, 'impact_score')}")
|
||||
|
||||
entities = _get(b, "entities_enriched", []) or []
|
||||
if entities:
|
||||
entities = _safe_get(b, "entities_enriched", [])
|
||||
if isinstance(entities, list) and entities:
|
||||
ent_str = ", ".join(
|
||||
f"{_get(e, 'name', '?')}({_get(e, 'sentiment_score', '?')})"
|
||||
for e in (entities[:5] if isinstance(entities, list) else [])
|
||||
f"{_safe_get(e, 'name', '?')}({_safe_get(e, 'sentiment_score', '?')})"
|
||||
for e in entities[:5]
|
||||
)
|
||||
result += f"Entities: {ent_str}\n"
|
||||
lines.append(f"Entities: {ent_str}")
|
||||
|
||||
ca = _get(b, "counter_argument", None)
|
||||
if ca:
|
||||
result += f"Counter-Argument: {str(ca)[:200]}...\n"
|
||||
ca = _safe_get(b, "counter_argument", None)
|
||||
if ca and ca != 'N/A':
|
||||
lines.append(f"Counter-Argument: {str(ca)[:200]}...")
|
||||
|
||||
result += "\n"
|
||||
lines.append("")
|
||||
|
||||
result = "\n".join(lines)
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
|
@ -421,7 +470,7 @@ def get_global_news(
|
|||
|
||||
client = _get_client()
|
||||
try:
|
||||
data = client.feed(per_page=20)
|
||||
data = client.feed(per_page=20, from_date=start_date, to_date=end_date)
|
||||
if hasattr(data, '__dict__') and not isinstance(data, dict):
|
||||
data = data.__dict__ if hasattr(data, '__dict__') else {}
|
||||
if isinstance(data, dict):
|
||||
|
|
@ -430,32 +479,50 @@ def get_global_news(
|
|||
briefs = getattr(data, 'briefs', [])
|
||||
except Exception as e:
|
||||
return f"Error fetching global news: {e}"
|
||||
result = f"# Global Intelligence Feed\n"
|
||||
result += f"# Source: Polaris Knowledge API\n"
|
||||
result += f"# Briefs: {len(briefs)}\n\n"
|
||||
|
||||
def _get2(obj, key, default='N/A'):
|
||||
if isinstance(obj, dict):
|
||||
return obj.get(key, default)
|
||||
return getattr(obj, key, default)
|
||||
|
||||
# Filter to requested date range (belt-and-suspenders)
|
||||
filtered = []
|
||||
for b in briefs:
|
||||
prov = _get2(b, "provenance", {})
|
||||
pub = str(_get2(b, 'published_at', ''))[:10]
|
||||
result += f"[{pub}] [{_get2(b, 'category', '')}] "
|
||||
result += f"{_get2(b, 'headline', '')} "
|
||||
result += f"(confidence={_get2(prov, 'confidence_score', '?')}, "
|
||||
result += f"bias={_get2(prov, 'bias_score', '?')}, "
|
||||
result += f"sentiment={_get2(b, 'sentiment', '?')})\n"
|
||||
pub = str(_safe_get(b, 'published_at', ''))[:10]
|
||||
if pub and start_date <= pub <= end_date:
|
||||
filtered.append(b)
|
||||
if not filtered:
|
||||
filtered = briefs # Fall back to unfiltered if date parsing fails
|
||||
|
||||
lines = [
|
||||
f"# Global Intelligence Feed ({start_date} to {end_date})",
|
||||
f"# Source: Polaris Knowledge API",
|
||||
f"# Briefs: {len(filtered)}",
|
||||
"",
|
||||
]
|
||||
|
||||
for b in filtered:
|
||||
prov = _safe_get(b, "provenance", {})
|
||||
if not isinstance(prov, dict):
|
||||
prov = {}
|
||||
pub = str(_safe_get(b, 'published_at', ''))[:10]
|
||||
lines.append(
|
||||
f"[{pub}] [{_safe_get(b, 'category', '')}] "
|
||||
f"{_safe_get(b, 'headline', '')} "
|
||||
f"(confidence={_safe_get(prov, 'confidence_score')}, "
|
||||
f"bias={_safe_get(prov, 'bias_score')}, "
|
||||
f"sentiment={_safe_get(b, 'sentiment')})"
|
||||
)
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
def get_insider_transactions(
|
||||
def get_sec_filings(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
) -> str:
|
||||
"""Fetch SEC EDGAR earnings filings via Polaris."""
|
||||
"""Fetch SEC EDGAR earnings filings (8-K, 10-Q, 10-K) via Polaris."""
|
||||
cache_key = f"sec_filings:{symbol}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
client = _get_client()
|
||||
try:
|
||||
data = client.transcripts(symbol, days=365)
|
||||
|
|
@ -463,18 +530,29 @@ def get_insider_transactions(
|
|||
return f"Error fetching filings for {symbol}: {e}"
|
||||
|
||||
filings = data.get("filings", [])
|
||||
result = f"# SEC Filings for {symbol.upper()}\n"
|
||||
result += f"# Source: Polaris Knowledge API (SEC EDGAR)\n\n"
|
||||
result += "Date,Form,Description,URL\n"
|
||||
for f in filings[:20]:
|
||||
result += f"{f.get('date', '')},{f.get('form', '')},{f.get('description', '')},{f.get('filing_url', '')}\n"
|
||||
lines = [
|
||||
f"# SEC Filings for {symbol.upper()}",
|
||||
f"# Source: Polaris Knowledge API (SEC EDGAR)",
|
||||
"",
|
||||
"Date,Form,Description,URL",
|
||||
]
|
||||
lines.extend(
|
||||
f"{_safe_get(f, 'date', '')},{_safe_get(f, 'form', '')},{_safe_get(f, 'description', '')},{_safe_get(f, 'filing_url', '')}"
|
||||
for f in filings[:20]
|
||||
)
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
# Keep old name as alias for backward compatibility
|
||||
get_insider_transactions = get_sec_filings
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Polaris-Exclusive: Sentiment & Trading Signals
|
||||
# (Not available from Yahoo Finance or Alpha Vantage)
|
||||
# (Complements price/fundamental data from yfinance and Alpha Vantage)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def get_sentiment_score(
|
||||
|
|
@ -488,7 +566,7 @@ def get_sentiment_score(
|
|||
- Coverage velocity (20% weight)
|
||||
- Event proximity (15% weight)
|
||||
|
||||
Not available from any other data vendor.
|
||||
Polaris-exclusive: complements price data from other vendors with intelligence signals.
|
||||
"""
|
||||
cache_key = f"sentiment:{symbol}"
|
||||
cached = _cached(cache_key)
|
||||
|
|
@ -501,24 +579,26 @@ def get_sentiment_score(
|
|||
except Exception as e:
|
||||
return f"Error fetching sentiment score for {symbol}: {e}"
|
||||
|
||||
result = f"# Composite Trading Signal: {symbol.upper()}\n"
|
||||
result += f"# Source: Polaris Knowledge API (exclusive)\n\n"
|
||||
result += f"Signal: {data.get('signal', 'N/A')}\n"
|
||||
result += f"Composite Score: {data.get('composite_score', 'N/A')}\n\n"
|
||||
|
||||
components = data.get("components", {})
|
||||
sent = components.get("sentiment", {})
|
||||
result += f"Sentiment (40%): current_24h={sent.get('current_24h')}, week_avg={sent.get('week_avg')}\n"
|
||||
sent = components.get("sentiment", {}) or {}
|
||||
mom = components.get("momentum", {}) or {}
|
||||
vol = components.get("volume", {}) or {}
|
||||
evt = components.get("events", {}) or {}
|
||||
|
||||
mom = components.get("momentum", {})
|
||||
result += f"Momentum (25%): {mom.get('direction', 'N/A')} (value={mom.get('value')})\n"
|
||||
|
||||
vol = components.get("volume", {})
|
||||
result += f"Volume (20%): {vol.get('briefs_24h')} briefs/24h, velocity={vol.get('velocity_change_pct')}%\n"
|
||||
|
||||
evt = components.get("events", {})
|
||||
result += f"Events (15%): {evt.get('count_7d')} events, latest={evt.get('latest_type')}\n"
|
||||
lines = [
|
||||
f"# Composite Trading Signal: {symbol.upper()}",
|
||||
f"# Source: Polaris Knowledge API (exclusive)",
|
||||
"",
|
||||
f"Signal: {_safe_get(data, 'signal')}",
|
||||
f"Composite Score: {_safe_get(data, 'composite_score')}",
|
||||
"",
|
||||
f"Sentiment (40%): current_24h={_safe_get(sent, 'current_24h')}, week_avg={_safe_get(sent, 'week_avg')}",
|
||||
f"Momentum (25%): {_safe_get(mom, 'direction')} (value={_safe_get(mom, 'value')})",
|
||||
f"Volume (20%): {_safe_get(vol, 'briefs_24h')} briefs/24h, velocity={_safe_get(vol, 'velocity_change_pct')}%",
|
||||
f"Events (15%): {_safe_get(evt, 'count_7d')} events, latest={_safe_get(evt, 'latest_type')}",
|
||||
]
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
|
@ -538,13 +618,21 @@ def get_sector_analysis(
|
|||
except Exception as e:
|
||||
return f"Error fetching sector analysis for {symbol}: {e}"
|
||||
|
||||
result = f"# Competitor Analysis: {symbol.upper()} ({data.get('sector', 'N/A')})\n"
|
||||
result += f"# Source: Polaris Knowledge API (exclusive)\n\n"
|
||||
result += "Ticker,Name,Price,RSI,Sentiment_7d,Briefs_7d\n"
|
||||
lines = [
|
||||
f"# Competitor Analysis: {symbol.upper()} ({_safe_get(data, 'sector')})",
|
||||
f"# Source: Polaris Knowledge API (exclusive)",
|
||||
"",
|
||||
"Ticker,Name,Price,RSI,Sentiment_7d,Briefs_7d",
|
||||
]
|
||||
|
||||
for c in data.get("competitors", []):
|
||||
result += f"{c.get('ticker')},{c.get('entity_name')},{c.get('price')},{c.get('rsi_14')},{c.get('sentiment_7d')},{c.get('briefs_7d')}\n"
|
||||
lines.append(
|
||||
f"{_safe_get(c, 'ticker')},{_safe_get(c, 'entity_name')},"
|
||||
f"{_safe_get(c, 'price')},{_safe_get(c, 'rsi_14')},"
|
||||
f"{_safe_get(c, 'sentiment_7d')},{_safe_get(c, 'briefs_7d')}"
|
||||
)
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
|
@ -564,19 +652,126 @@ def get_news_impact(
|
|||
except Exception as e:
|
||||
return f"Error fetching news impact for {symbol}: {e}"
|
||||
|
||||
result = f"# News Impact Analysis: {symbol.upper()}\n"
|
||||
result += f"# Source: Polaris Knowledge API (exclusive)\n\n"
|
||||
result += f"Briefs Analyzed: {data.get('briefs_analyzed', 0)}\n"
|
||||
result += f"Avg 1-Day Impact: {data.get('avg_impact_1d_pct', 'N/A')}%\n"
|
||||
result += f"Avg 3-Day Impact: {data.get('avg_impact_3d_pct', 'N/A')}%\n\n"
|
||||
best = data.get("best_impact", {}) or {}
|
||||
worst = data.get("worst_impact", {}) or {}
|
||||
|
||||
lines = [
|
||||
f"# News Impact Analysis: {symbol.upper()}",
|
||||
f"# Source: Polaris Knowledge API (exclusive)",
|
||||
"",
|
||||
f"Briefs Analyzed: {_safe_get(data, 'briefs_analyzed', 0)}",
|
||||
f"Avg 1-Day Impact: {_safe_get(data, 'avg_impact_1d_pct')}%",
|
||||
f"Avg 3-Day Impact: {_safe_get(data, 'avg_impact_3d_pct')}%",
|
||||
"",
|
||||
]
|
||||
|
||||
best = data.get("best_impact", {})
|
||||
if best:
|
||||
result += f"Best Impact: {best.get('headline', '')[:60]} (+{best.get('impact_1d_pct')}%)\n"
|
||||
|
||||
worst = data.get("worst_impact", {})
|
||||
lines.append(f"Best Impact: {_safe_get(best, 'headline', '')[:60]} (+{_safe_get(best, 'impact_1d_pct')}%)")
|
||||
if worst:
|
||||
result += f"Worst Impact: {worst.get('headline', '')[:60]} ({worst.get('impact_1d_pct')}%)\n"
|
||||
lines.append(f"Worst Impact: {_safe_get(worst, 'headline', '')[:60]} ({_safe_get(worst, 'impact_1d_pct')}%)")
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Polaris-Exclusive: Technical Analysis & Competitive Intelligence
|
||||
# (Phase 2 — additional intelligence capabilities)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def get_technicals(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
) -> str:
|
||||
"""Get full technical analysis with 20 indicators and buy/sell/neutral signal.
|
||||
|
||||
Returns all indicators at once: SMA, EMA, RSI, MACD, Bollinger, ATR,
|
||||
Stochastic, ADX, OBV, VWAP, Williams %R, CCI, MFI, ROC, and more.
|
||||
Includes a composite signal summary with buy/sell/neutral recommendation.
|
||||
|
||||
Polaris-exclusive: complements price data from other vendors with intelligence signals.
|
||||
"""
|
||||
cache_key = f"technicals:{symbol}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
client = _get_client()
|
||||
try:
|
||||
data = client.technicals(symbol, range="6mo")
|
||||
except Exception as e:
|
||||
return f"Error fetching technicals for {symbol}: {e}"
|
||||
|
||||
latest = data.get("latest", {}) or {}
|
||||
signal = data.get("signal_summary", {}) or {}
|
||||
|
||||
lines = [
|
||||
f"# Technical Analysis: {symbol.upper()}",
|
||||
f"# Source: Polaris Knowledge API (exclusive — 20 indicators)",
|
||||
"",
|
||||
f"Signal: {_safe_get(signal, 'overall', 'N/A').upper()}",
|
||||
f"Buy signals: {_safe_get(signal, 'buy_count', 0)} | Sell signals: {_safe_get(signal, 'sell_count', 0)} | Neutral: {_safe_get(signal, 'neutral_count', 0)}",
|
||||
"",
|
||||
f"Price: {_safe_get(latest, 'price')}",
|
||||
f"RSI(14): {_safe_get(latest, 'rsi_14')}",
|
||||
f"MACD: {_safe_get(latest.get('macd', {}), 'macd')} (signal={_safe_get(latest.get('macd', {}), 'signal')}, hist={_safe_get(latest.get('macd', {}), 'histogram')})",
|
||||
f"SMA(20): {_safe_get(latest, 'sma_20')} | SMA(50): {_safe_get(latest, 'sma_50')}",
|
||||
f"EMA(12): {_safe_get(latest, 'ema_12')} | EMA(26): {_safe_get(latest, 'ema_26')}",
|
||||
f"Bollinger: upper={_safe_get(latest.get('bollinger', {}), 'upper')}, middle={_safe_get(latest.get('bollinger', {}), 'middle')}, lower={_safe_get(latest.get('bollinger', {}), 'lower')}",
|
||||
f"ATR(14): {_safe_get(latest, 'atr_14')}",
|
||||
f"Stochastic: K={_safe_get(latest.get('stochastic', {}), 'k')}, D={_safe_get(latest.get('stochastic', {}), 'd')}",
|
||||
f"ADX(14): {_safe_get(latest, 'adx_14')}",
|
||||
f"Williams %R(14): {_safe_get(latest, 'williams_r_14')}",
|
||||
f"CCI(20): {_safe_get(latest, 'cci_20')}",
|
||||
f"MFI(14): {_safe_get(latest, 'mfi_14')}",
|
||||
f"ROC(12): {_safe_get(latest, 'roc_12')}",
|
||||
f"OBV: {_safe_get(latest, 'obv')}",
|
||||
f"VWAP: {_safe_get(latest, 'vwap')}",
|
||||
]
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
def get_competitors(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
) -> str:
|
||||
"""Get same-sector peers with live price, RSI, sentiment, and news coverage.
|
||||
|
||||
Returns competitors ranked by relevance with real-time data for
|
||||
relative analysis and sector positioning.
|
||||
|
||||
Polaris-exclusive: complements price data from other vendors with intelligence signals.
|
||||
"""
|
||||
cache_key = f"peer_analysis:{symbol}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
client = _get_client()
|
||||
try:
|
||||
data = client.competitors(symbol)
|
||||
except Exception as e:
|
||||
return f"Error fetching competitors for {symbol}: {e}"
|
||||
|
||||
peers = data.get("competitors", [])
|
||||
lines = [
|
||||
f"# Peer Analysis: {symbol.upper()} ({_safe_get(data, 'sector')})",
|
||||
f"# Source: Polaris Knowledge API (exclusive)",
|
||||
f"# Peers: {len(peers)}",
|
||||
"",
|
||||
"Ticker,Name,Price,Change%,RSI(14),Sentiment_7d,Briefs_7d,Signal",
|
||||
]
|
||||
|
||||
for c in peers:
|
||||
lines.append(
|
||||
f"{_safe_get(c, 'ticker')},{_safe_get(c, 'entity_name')},"
|
||||
f"${_safe_get(c, 'price')},{_safe_get(c, 'change_pct')}%,"
|
||||
f"{_safe_get(c, 'rsi_14')},{_safe_get(c, 'sentiment_7d')},"
|
||||
f"{_safe_get(c, 'briefs_7d')},{_safe_get(c, 'signal', 'N/A')}"
|
||||
)
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
|
|
|||
Loading…
Reference in New Issue