diff --git a/tradingagents/dataflows/interface.py b/tradingagents/dataflows/interface.py index 09554db5..4e2f45e8 100644 --- a/tradingagents/dataflows/interface.py +++ b/tradingagents/dataflows/interface.py @@ -36,6 +36,8 @@ from .polaris import ( get_sentiment_score as get_polaris_sentiment_score, get_sector_analysis as get_polaris_sector_analysis, get_news_impact as get_polaris_news_impact, + get_technicals as get_polaris_technicals, + get_competitors as get_polaris_competitors, ) # Configuration and routing logic @@ -149,6 +151,12 @@ VENDOR_METHODS = { "get_news_impact": { "polaris": get_polaris_news_impact, }, + "get_technicals": { + "polaris": get_polaris_technicals, + }, + "get_competitors": { + "polaris": get_polaris_competitors, + }, } def get_category_for_method(method: str) -> str: diff --git a/tradingagents/dataflows/polaris.py b/tradingagents/dataflows/polaris.py index ac3aa079..8e0befda 100644 --- a/tradingagents/dataflows/polaris.py +++ b/tradingagents/dataflows/polaris.py @@ -70,12 +70,41 @@ def _cached(key: str): return _cache.get(key) -def _set_cache(key: str, data: str): +def _set_cache(key: str, data): """Store data in cache (thread-safe).""" with _cache_lock: _cache[key] = data +# --------------------------------------------------------------------------- +# Shared helpers +# --------------------------------------------------------------------------- + +def _safe_get(obj, key, default='N/A'): + """Get attribute from dict or object, returning default if missing or None.""" + if isinstance(obj, dict): + val = obj.get(key, default) + return default if val is None else val + val = getattr(obj, key, default) + return default if val is None else val + + +def _days_to_range(days: int) -> str: + """Convert a day count to a Polaris range string.""" + if days <= 30: + return "1mo" + elif days <= 90: + return "3mo" + elif days <= 180: + return "6mo" + elif days <= 365: + return "1y" + elif days <= 730: + return "2y" + else: + return "5y" + + # --------------------------------------------------------------------------- # Core Stock APIs # --------------------------------------------------------------------------- @@ -93,23 +122,10 @@ def get_stock_data( client = _get_client() - # Determine range from date span start = datetime.strptime(start_date, "%Y-%m-%d") end = datetime.strptime(end_date, "%Y-%m-%d") days = (end - start).days - - if days <= 30: - range_param = "1mo" - elif days <= 90: - range_param = "3mo" - elif days <= 180: - range_param = "6mo" - elif days <= 365: - range_param = "1y" - elif days <= 730: - range_param = "2y" - else: - range_param = "5y" + range_param = _days_to_range(days) try: data = client.candles(symbol, interval="1d", range=range_param) @@ -123,16 +139,19 @@ def get_stock_data( # Filter to requested date range candles = [c for c in candles if start_date <= c["date"] <= end_date] - # Format as CSV (matching yfinance output format) - header = f"# Stock data for {symbol.upper()} from {start_date} to {end_date}\n" - header += f"# Source: Polaris Knowledge API (multi-provider: Yahoo/TwelveData/FMP)\n" - header += f"# Total records: {len(candles)}\n\n" + lines = [ + f"# Stock data for {symbol.upper()} from {start_date} to {end_date}", + f"# Source: Polaris Knowledge API (multi-provider: Yahoo/TwelveData/FMP)", + f"# Total records: {len(candles)}", + "", + "Date,Open,High,Low,Close,Volume", + ] + lines.extend( + f"{c['date']},{c['open']},{c['high']},{c['low']},{c['close']},{c['volume']}" + for c in candles + ) - csv = "Date,Open,High,Low,Close,Volume\n" - for c in candles: - csv += f"{c['date']},{c['open']},{c['high']},{c['low']},{c['close']},{c['volume']}\n" - - result = header + csv + result = "\n".join(lines) + "\n" _set_cache(cache_key, result) return result @@ -169,23 +188,17 @@ def get_indicators( } polaris_type = indicator_map.get(indicator.lower(), indicator.lower()) + range_param = _days_to_range(look_back_days) - # Determine range - if look_back_days <= 30: - range_param = "1mo" - elif look_back_days <= 90: - range_param = "3mo" - elif look_back_days <= 180: - range_param = "6mo" - else: - range_param = "1y" + known_types = { + "sma", "ema", "rsi", "macd", "bollinger", "atr", + "stochastic", "adx", "obv", "vwap", "williams_r", + "cci", "mfi", "roc", "ppo", "trix", "donchian", + "parabolic_sar", "ichimoku", "fibonacci", + } - # Try specific indicator first, fall back to full technicals try: - if polaris_type in ["sma", "ema", "rsi", "macd", "bollinger", "atr", - "stochastic", "adx", "obv", "vwap", "williams_r", - "cci", "mfi", "roc", "ppo", "trix", "donchian", - "parabolic_sar", "ichimoku", "fibonacci"]: + if polaris_type in known_types: data = client.indicators(symbol, type=polaris_type, range=range_param) else: data = client.technicals(symbol, range=range_param) @@ -194,38 +207,39 @@ def get_indicators( values = data.get("values", []) - header = f"# Technical Indicator: {indicator} for {symbol.upper()}\n" - header += f"# Source: Polaris Knowledge API\n" - header += f"# Period: {range_param} | Data points: {len(values)}\n\n" + lines = [ + f"# Technical Indicator: {indicator} for {symbol.upper()}", + f"# Source: Polaris Knowledge API", + f"# Period: {range_param} | Data points: {len(values) if isinstance(values, list) else 'N/A'}", + "", + ] if isinstance(values, list) and values: - # Format based on indicator type first = values[0] if "value" in first: - csv = "Date,Value\n" - for v in values: - csv += f"{v['date']},{v['value']}\n" + lines.append("Date,Value") + lines.extend(f"{v['date']},{v.get('value', '')}" for v in values) elif "macd" in first: - csv = "Date,MACD,Signal,Histogram\n" - for v in values: - csv += f"{v['date']},{v.get('macd','')},{v.get('signal','')},{v.get('histogram','')}\n" + lines.append("Date,MACD,Signal,Histogram") + lines.extend(f"{v['date']},{v.get('macd', '')},{v.get('signal', '')},{v.get('histogram', '')}" for v in values) elif "upper" in first: - csv = "Date,Upper,Middle,Lower\n" - for v in values: - csv += f"{v['date']},{v.get('upper','')},{v.get('middle','')},{v.get('lower','')}\n" + lines.append("Date,Upper,Middle,Lower") + lines.extend(f"{v['date']},{v.get('upper', '')},{v.get('middle', '')},{v.get('lower', '')}" for v in values) elif "k" in first: - csv = "Date,K,D\n" - for v in values: - csv += f"{v['date']},{v.get('k','')},{v.get('d','')}\n" + lines.append("Date,K,D") + lines.extend(f"{v['date']},{v.get('k', '')},{v.get('d', '')}" for v in values) else: - csv = str(values) + # Format dict keys as CSV columns + keys = list(first.keys()) + lines.append(",".join(keys)) + lines.extend(",".join(str(v.get(k, '')) for k in keys) for v in values) elif isinstance(values, dict): - # Fibonacci or similar - csv = str(values) + for k, v in values.items(): + lines.append(f"{k}: {v}") else: - csv = "No indicator data available" + lines.append("No indicator data available") - result = header + csv + result = "\n".join(lines) + "\n" _set_cache(cache_key, result) return result @@ -260,23 +274,27 @@ def get_fundamentals( except Exception as e: return f"Error fetching fundamentals for {symbol}: {e}" - result = f"# Company Fundamentals: {data.get('company_name', symbol)}\n" - result += f"# Source: Polaris Knowledge API\n\n" - result += f"Sector: {data.get('sector', 'N/A')}\n" - result += f"Industry: {data.get('industry', 'N/A')}\n" - result += f"Market Cap: {data.get('market_cap_formatted', 'N/A')}\n" - result += f"P/E Ratio: {data.get('pe_ratio', 'N/A')}\n" - result += f"Forward P/E: {data.get('forward_pe', 'N/A')}\n" - result += f"EPS: {data.get('eps', 'N/A')}\n" - result += f"Revenue: {data.get('revenue_formatted', 'N/A')}\n" - result += f"EBITDA: {data.get('ebitda_formatted', 'N/A')}\n" - result += f"Profit Margin: {data.get('profit_margin', 'N/A')}\n" - result += f"Debt/Equity: {data.get('debt_to_equity', 'N/A')}\n" - result += f"ROE: {data.get('return_on_equity', 'N/A')}\n" - result += f"Beta: {data.get('beta', 'N/A')}\n" - result += f"52-Week High: {data.get('fifty_two_week_high', 'N/A')}\n" - result += f"52-Week Low: {data.get('fifty_two_week_low', 'N/A')}\n" + lines = [ + f"# Company Fundamentals: {data.get('company_name', symbol)}", + f"# Source: Polaris Knowledge API", + "", + f"Sector: {_safe_get(data, 'sector')}", + f"Industry: {_safe_get(data, 'industry')}", + f"Market Cap: {_safe_get(data, 'market_cap_formatted')}", + f"P/E Ratio: {_safe_get(data, 'pe_ratio')}", + f"Forward P/E: {_safe_get(data, 'forward_pe')}", + f"EPS: {_safe_get(data, 'eps')}", + f"Revenue: {_safe_get(data, 'revenue_formatted')}", + f"EBITDA: {_safe_get(data, 'ebitda_formatted')}", + f"Profit Margin: {_safe_get(data, 'profit_margin')}", + f"Debt/Equity: {_safe_get(data, 'debt_to_equity')}", + f"ROE: {_safe_get(data, 'return_on_equity')}", + f"Beta: {_safe_get(data, 'beta')}", + f"52-Week High: {_safe_get(data, 'fifty_two_week_high')}", + f"52-Week Low: {_safe_get(data, 'fifty_two_week_low')}", + ] + result = "\n".join(lines) + "\n" _set_cache(cache_key, result) return result @@ -285,17 +303,27 @@ def get_balance_sheet( symbol: Annotated[str, "ticker symbol of the company"], ) -> str: """Fetch balance sheet from Polaris.""" + cache_key = f"balance_sheet:{symbol}" + cached = _cached(cache_key) + if cached: + return cached + try: data = _get_financials_cached(symbol) except Exception as e: return f"Error fetching balance sheet for {symbol}: {e}" sheets = data.get("balance_sheets", []) - result = f"# Balance Sheet: {symbol.upper()}\n# Source: Polaris Knowledge API\n\n" - result += "Date,Total Assets,Total Liabilities,Total Equity\n" - for s in sheets: - result += f"{s['date']},{s['total_assets']},{s['total_liabilities']},{s['total_equity']}\n" + lines = [ + f"# Balance Sheet: {symbol.upper()}", + f"# Source: Polaris Knowledge API", + "", + "Date,Total Assets,Total Liabilities,Total Equity", + ] + lines.extend(f"{s['date']},{s['total_assets']},{s['total_liabilities']},{s['total_equity']}" for s in sheets) + result = "\n".join(lines) + "\n" + _set_cache(cache_key, result) return result @@ -303,13 +331,25 @@ def get_cashflow( symbol: Annotated[str, "ticker symbol of the company"], ) -> str: """Fetch cash flow data from Polaris.""" + cache_key = f"cashflow:{symbol}" + cached = _cached(cache_key) + if cached: + return cached + try: data = _get_financials_cached(symbol) except Exception as e: return f"Error fetching cashflow for {symbol}: {e}" - result = f"# Cash Flow: {symbol.upper()}\n# Source: Polaris Knowledge API\n\n" - result += f"Free Cash Flow: {data.get('free_cash_flow', 'N/A')}\n" + lines = [ + f"# Cash Flow: {symbol.upper()}", + f"# Source: Polaris Knowledge API", + "", + f"Free Cash Flow: {_safe_get(data, 'free_cash_flow')}", + ] + + result = "\n".join(lines) + "\n" + _set_cache(cache_key, result) return result @@ -317,17 +357,27 @@ def get_income_statement( symbol: Annotated[str, "ticker symbol of the company"], ) -> str: """Fetch income statement from Polaris.""" + cache_key = f"income_stmt:{symbol}" + cached = _cached(cache_key) + if cached: + return cached + try: data = _get_financials_cached(symbol) except Exception as e: return f"Error fetching income statement for {symbol}: {e}" stmts = data.get("income_statements", []) - result = f"# Income Statement: {symbol.upper()}\n# Source: Polaris Knowledge API\n\n" - result += "Date,Revenue,Net Income,Gross Profit\n" - for s in stmts: - result += f"{s['date']},{s['revenue']},{s['net_income']},{s['gross_profit']}\n" + lines = [ + f"# Income Statement: {symbol.upper()}", + f"# Source: Polaris Knowledge API", + "", + "Date,Revenue,Net Income,Gross Profit", + ] + lines.extend(f"{s['date']},{s['revenue']},{s['net_income']},{s['gross_profit']}" for s in stmts) + result = "\n".join(lines) + "\n" + _set_cache(cache_key, result) return result @@ -355,8 +405,7 @@ def get_news( client = _get_client() try: - data = client.search(symbol, per_page=20) - # Handle both dict and typed response objects + data = client.search(symbol, 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): @@ -366,45 +415,45 @@ def get_news( except Exception as e: return f"Error fetching news for {symbol}: {e}" if not briefs: - return f"No intelligence briefs found for {symbol}" + return f"No intelligence briefs found for {symbol} between {start_date} and {end_date}" - result = f"# Intelligence Briefs for {symbol.upper()}\n" - result += f"# Source: Polaris Knowledge API (sentiment-scored, bias-analyzed)\n" - result += f"# Total: {len(briefs)} briefs\n\n" - - def _get(obj, key, default='N/A'): - """Get attribute from dict or object.""" - if isinstance(obj, dict): - return obj.get(key, default) - return getattr(obj, key, default) + lines = [ + f"# Intelligence Briefs for {symbol.upper()} ({start_date} to {end_date})", + f"# Source: Polaris Knowledge API (sentiment-scored, bias-analyzed)", + f"# Total: {len(briefs)} briefs", + "", + ] for b in briefs: - prov = _get(b, "provenance", {}) - result += f"--- Brief: {_get(b, 'id', '')} ---\n" - result += f"Date: {_get(b, 'published_at', '')}\n" - result += f"Headline: {_get(b, 'headline', '')}\n" - result += f"Summary: {_get(b, 'summary', '')}\n" - result += f"Category: {_get(b, 'category', '')}\n" - result += f"Confidence: {_get(prov, 'confidence_score', 'N/A')}\n" - result += f"Bias Score: {_get(prov, 'bias_score', 'N/A')}\n" - result += f"Review Status: {_get(prov, 'review_status', 'N/A')}\n" - result += f"Sentiment: {_get(b, 'sentiment', 'N/A')}\n" - 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