Merge f7f0aa0678 into fa4d01c23a
This commit is contained in:
Johnny
GitHub
commit
7ea1bd4c0b
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@ -1 +1,3 @@
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.
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polaris-news>=0.6.0
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cachetools>=5.0.0
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@ -23,6 +23,21 @@ from .alpha_vantage import (
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get_global_news as get_alpha_vantage_global_news,
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)
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from .alpha_vantage_common import AlphaVantageRateLimitError
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from .polaris import (
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get_stock_data as get_polaris_stock,
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get_indicators as get_polaris_indicators,
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get_fundamentals as get_polaris_fundamentals,
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get_balance_sheet as get_polaris_balance_sheet,
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get_cashflow as get_polaris_cashflow,
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get_income_statement as get_polaris_income_statement,
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get_sec_filings as get_polaris_sec_filings,
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get_news as get_polaris_news,
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get_global_news as get_polaris_global_news,
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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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)
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# Configuration and routing logic
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from .config import get_config
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@ -38,7 +53,8 @@ TOOLS_CATEGORIES = {
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"technical_indicators": {
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"description": "Technical analysis indicators",
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"tools": [
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"get_indicators"
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"get_indicators",
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"get_technicals"
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]
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},
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"fundamental_data": {
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@ -56,6 +72,15 @@ TOOLS_CATEGORIES = {
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"get_news",
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"get_global_news",
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"get_insider_transactions",
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"get_sec_filings",
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]
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},
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"sentiment_analysis": {
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"description": "Sentiment scoring, trading signals, and news impact (Polaris-exclusive)",
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"tools": [
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"get_sentiment_score",
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"get_sector_analysis",
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"get_news_impact",
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]
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}
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}
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@ -63,6 +88,7 @@ TOOLS_CATEGORIES = {
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VENDOR_LIST = [
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"yfinance",
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"alpha_vantage",
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"polaris",
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]
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# Mapping of methods to their vendor-specific implementations
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@ -71,42 +97,66 @@ VENDOR_METHODS = {
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"get_stock_data": {
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"alpha_vantage": get_alpha_vantage_stock,
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"yfinance": get_YFin_data_online,
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"polaris": get_polaris_stock,
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},
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# technical_indicators
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"get_indicators": {
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"alpha_vantage": get_alpha_vantage_indicator,
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"yfinance": get_stock_stats_indicators_window,
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"polaris": get_polaris_indicators,
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},
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# fundamental_data
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"get_fundamentals": {
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"alpha_vantage": get_alpha_vantage_fundamentals,
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"yfinance": get_yfinance_fundamentals,
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"polaris": get_polaris_fundamentals,
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},
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"get_balance_sheet": {
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"alpha_vantage": get_alpha_vantage_balance_sheet,
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"yfinance": get_yfinance_balance_sheet,
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"polaris": get_polaris_balance_sheet,
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},
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"get_cashflow": {
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"alpha_vantage": get_alpha_vantage_cashflow,
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"yfinance": get_yfinance_cashflow,
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"polaris": get_polaris_cashflow,
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},
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"get_income_statement": {
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"alpha_vantage": get_alpha_vantage_income_statement,
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"yfinance": get_yfinance_income_statement,
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"polaris": get_polaris_income_statement,
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},
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# news_data
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"get_news": {
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"alpha_vantage": get_alpha_vantage_news,
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"yfinance": get_news_yfinance,
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"polaris": get_polaris_news,
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},
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"get_global_news": {
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"yfinance": get_global_news_yfinance,
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"alpha_vantage": get_alpha_vantage_global_news,
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"polaris": get_polaris_global_news,
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},
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"get_insider_transactions": {
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"alpha_vantage": get_alpha_vantage_insider_transactions,
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"yfinance": get_yfinance_insider_transactions,
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},
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"get_sec_filings": {
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"polaris": get_polaris_sec_filings,
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},
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# sentiment_analysis (Polaris-exclusive)
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"get_sentiment_score": {
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"polaris": get_polaris_sentiment_score,
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},
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"get_sector_analysis": {
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"polaris": get_polaris_sector_analysis,
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},
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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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}
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def get_category_for_method(method: str) -> str:
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@ -0,0 +1,761 @@
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"""
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Polaris Knowledge API data vendor for TradingAgents.
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Polaris provides sentiment-scored intelligence briefs, composite trading signals,
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technical indicators, financial data, and news impact analysis. Unlike raw data
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feeds, every Polaris response includes confidence scores, bias analysis, and
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NLP-derived metadata that enriches agent decision-making.
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Setup:
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pip install polaris-news cachetools
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export POLARIS_API_KEY=pr_live_xxx # Free: 1,000 credits/month at thepolarisreport.com
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API docs: https://thepolarisreport.com/api-reference
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"""
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import os
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import threading
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from typing import Annotated
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from datetime import datetime
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from cachetools import TTLCache
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# ---------------------------------------------------------------------------
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# Configuration
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# ---------------------------------------------------------------------------
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_CACHE_TTL = 300 # 5 minutes
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_CACHE_MAX = 500
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_cache = TTLCache(maxsize=_CACHE_MAX, ttl=_CACHE_TTL)
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_cache_lock = threading.Lock()
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_client_instance = None
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_client_lock = threading.Lock()
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def _get_client():
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"""Lazy-initialize Polaris client (thread-safe singleton)."""
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global _client_instance
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if _client_instance is not None:
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return _client_instance
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with _client_lock:
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if _client_instance is not None:
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return _client_instance
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try:
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from polaris_news import PolarisClient
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except ImportError:
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raise ImportError(
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"polaris-news is required for the Polaris data vendor. "
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"Install it with: pip install polaris-news"
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)
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api_key = os.environ.get("POLARIS_API_KEY")
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if not api_key:
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raise EnvironmentError(
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"POLARIS_API_KEY environment variable is required. "
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"Get a free key at https://thepolarisreport.com/pricing"
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)
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_client_instance = PolarisClient(api_key=api_key)
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return _client_instance
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def _cached(key: str):
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"""Check cache for a key. Returns cached value or None (thread-safe)."""
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with _cache_lock:
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return _cache.get(key)
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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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def _extract_briefs(data) -> list:
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"""Extract briefs list from API response (handles both dict and typed objects)."""
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if not isinstance(data, dict):
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data = vars(data) if hasattr(data, '__dict__') else {}
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return data.get("briefs", [])
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# ---------------------------------------------------------------------------
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# Core Stock APIs
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# ---------------------------------------------------------------------------
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def get_stock_data(
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symbol: Annotated[str, "ticker symbol of the company"],
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start_date: Annotated[str, "Start date in yyyy-mm-dd format"],
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end_date: Annotated[str, "End date in yyyy-mm-dd format"],
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) -> str:
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"""Fetch OHLCV stock data from Polaris (via multi-provider: Yahoo/TwelveData/FMP)."""
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cache_key = f"stock:{symbol}:{start_date}:{end_date}"
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cached = _cached(cache_key)
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if cached:
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return cached
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client = _get_client()
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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 <= 0:
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return f"Invalid date range: start_date ({start_date}) must be before end_date ({end_date})"
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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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except Exception as e:
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return f"Error fetching stock data for {symbol}: {e}"
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candles = data.get("candles", [])
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if not candles:
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return f"No data found for symbol '{symbol}' between {start_date} and {end_date}"
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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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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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result = "\n".join(lines) + "\n"
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_set_cache(cache_key, result)
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return result
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# ---------------------------------------------------------------------------
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# Technical Indicators
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# ---------------------------------------------------------------------------
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def get_indicators(
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symbol: Annotated[str, "ticker symbol of the company"],
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indicator: Annotated[str, "technical indicator to get"],
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curr_date: Annotated[str, "Current trading date, YYYY-mm-dd"],
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look_back_days: Annotated[int, "how many days to look back"],
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) -> str:
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"""Fetch technical indicators from Polaris (20 indicators + signal summary).
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Uses curr_date and look_back_days to determine the data range.
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"""
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cache_key = f"indicators:{symbol}:{indicator}:{curr_date}:{look_back_days}"
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cached = _cached(cache_key)
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if cached:
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return cached
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client = _get_client()
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# Use curr_date to determine if we need historical vs current data
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today = datetime.now().strftime("%Y-%m-%d")
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is_historical = curr_date < today if curr_date else False
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# Map common indicator names to Polaris types
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indicator_map = {
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"close_50_sma": "sma", "close_20_sma": "sma", "close_200_sma": "sma",
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"rsi_14": "rsi", "rsi": "rsi",
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"macd": "macd", "macds": "macd", "macdh": "macd",
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"boll": "bollinger", "boll_ub": "bollinger", "boll_lb": "bollinger",
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"atr": "atr", "atr_14": "atr",
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"stoch": "stochastic", "stochrsi": "stochastic",
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"adx": "adx", "williams_r": "williams_r",
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"cci": "cci", "mfi": "mfi", "roc": "roc",
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"obv": "obv", "vwap": "vwap",
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}
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polaris_type = indicator_map.get(indicator.lower(), indicator.lower())
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# If historical, we need enough range to cover curr_date - look_back_days
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||||
if is_historical:
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days_from_now = (datetime.strptime(today, "%Y-%m-%d") - datetime.strptime(curr_date, "%Y-%m-%d")).days
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range_param = _days_to_range(days_from_now + look_back_days)
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else:
|
||||
range_param = _days_to_range(look_back_days)
|
||||
|
||||
known_types = {
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"sma", "ema", "rsi", "macd", "bollinger", "atr",
|
||||
"stochastic", "adx", "obv", "vwap", "williams_r",
|
||||
"cci", "mfi", "roc", "ppo", "trix", "donchian",
|
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"parabolic_sar", "ichimoku", "fibonacci",
|
||||
}
|
||||
|
||||
try:
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||||
if polaris_type in known_types:
|
||||
data = client.indicators(symbol, type=polaris_type, range=range_param)
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||||
else:
|
||||
# Unknown indicator — return an error rather than silently falling back
|
||||
# to client.technicals() which returns a different structure
|
||||
return (
|
||||
f"Unknown indicator '{indicator}' for {symbol}. "
|
||||
f"Supported: {', '.join(sorted(known_types))}"
|
||||
)
|
||||
except Exception as e:
|
||||
return f"Error fetching indicators for {symbol}: {e}"
|
||||
|
||||
values = data.get("values", [])
|
||||
|
||||
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:
|
||||
first = values[0]
|
||||
if "value" in first:
|
||||
lines.append("Date,Value")
|
||||
lines.extend(f"{v['date']},{v.get('value', '')}" for v in values)
|
||||
elif "macd" in first:
|
||||
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:
|
||||
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:
|
||||
lines.append("Date,K,D")
|
||||
lines.extend(f"{v['date']},{v.get('k', '')},{v.get('d', '')}" for v in values)
|
||||
else:
|
||||
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):
|
||||
for k, v in values.items():
|
||||
lines.append(f"{k}: {v}")
|
||||
else:
|
||||
lines.append("No indicator data available")
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Fundamental Data
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _get_financials_cached(symbol: str) -> dict:
|
||||
"""Shared cached financials fetch — used by fundamentals, balance_sheet, cashflow, income_statement."""
|
||||
cache_key = f"financials_raw:{symbol}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
client = _get_client()
|
||||
data = client.financials(symbol)
|
||||
_set_cache(cache_key, data)
|
||||
return data
|
||||
|
||||
|
||||
def get_fundamentals(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
) -> str:
|
||||
"""Fetch company fundamentals from Polaris (via Yahoo Finance quoteSummary)."""
|
||||
cache_key = f"fundamentals:{symbol}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
try:
|
||||
data = _get_financials_cached(symbol)
|
||||
except Exception as e:
|
||||
return f"Error fetching fundamentals for {symbol}: {e}"
|
||||
|
||||
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
|
||||
|
||||
|
||||
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", [])
|
||||
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
|
||||
|
||||
|
||||
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}"
|
||||
|
||||
statements = data.get("cash_flow_statements", [])
|
||||
lines = [
|
||||
f"# Cash Flow: {symbol.upper()}",
|
||||
f"# Source: Polaris Knowledge API",
|
||||
"",
|
||||
]
|
||||
if statements:
|
||||
lines.append("Date,Operating Cash Flow,Capital Expenditure,Free Cash Flow")
|
||||
lines.extend(
|
||||
f"{s.get('date', '')},{s.get('operating_cash_flow', '')},{s.get('capital_expenditure', '')},{s.get('free_cash_flow', '')}"
|
||||
for s in statements
|
||||
)
|
||||
else:
|
||||
lines.append(f"Free Cash Flow: {_safe_get(data, 'free_cash_flow')}")
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
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", [])
|
||||
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
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# News & Intelligence (Polaris advantage — sentiment-scored, not raw headlines)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _format_brief_detail(b, lines: list) -> None:
|
||||
"""Format a single brief into output lines (shared by get_news)."""
|
||||
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 = _safe_get(b, "entities_enriched", [])
|
||||
if isinstance(entities, list) and entities:
|
||||
ent_str = ", ".join(
|
||||
f"{_safe_get(e, 'name', '?')}({_safe_get(e, 'sentiment_score', '?')})"
|
||||
for e in entities[:5]
|
||||
)
|
||||
lines.append(f"Entities: {ent_str}")
|
||||
|
||||
ca = _safe_get(b, "counter_argument", None)
|
||||
if ca and ca != 'N/A':
|
||||
lines.append(f"Counter-Argument: {str(ca)[:200]}...")
|
||||
|
||||
lines.append("")
|
||||
|
||||
|
||||
def get_news(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
start_date: Annotated[str, "Start date in yyyy-mm-dd format"],
|
||||
end_date: Annotated[str, "End date in yyyy-mm-dd format"],
|
||||
) -> str:
|
||||
"""Fetch sentiment-scored intelligence briefs from Polaris.
|
||||
|
||||
Unlike raw news feeds, each brief includes:
|
||||
- Confidence score (0-1)
|
||||
- Bias score and direction
|
||||
- Counter-arguments
|
||||
- Entity-level sentiment (-1.0 to +1.0)
|
||||
"""
|
||||
cache_key = f"news:{symbol}:{start_date}:{end_date}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
client = _get_client()
|
||||
try:
|
||||
data = client.search(symbol, per_page=20, from_date=start_date, to_date=end_date)
|
||||
briefs = _extract_briefs(data)
|
||||
except Exception as e:
|
||||
return f"Error fetching news for {symbol}: {e}"
|
||||
if not briefs:
|
||||
return f"No intelligence briefs found for {symbol} between {start_date} and {end_date}"
|
||||
|
||||
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:
|
||||
_format_brief_detail(b, lines)
|
||||
|
||||
result = "\n".join(lines) + "\n"
|
||||
_set_cache(cache_key, result)
|
||||
return result
|
||||
|
||||
|
||||
def get_global_news(
|
||||
start_date: Annotated[str, "Start date in yyyy-mm-dd format"],
|
||||
end_date: Annotated[str, "End date in yyyy-mm-dd format"],
|
||||
) -> str:
|
||||
"""Fetch global intelligence feed from Polaris with sentiment and bias scoring."""
|
||||
cache_key = f"global_news:{start_date}:{end_date}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
client = _get_client()
|
||||
try:
|
||||
data = client.feed(per_page=20, from_date=start_date, to_date=end_date)
|
||||
briefs = _extract_briefs(data)
|
||||
except Exception as e:
|
||||
return f"Error fetching global news: {e}"
|
||||
|
||||
if not briefs:
|
||||
return f"No intelligence briefs found between {start_date} and {end_date}"
|
||||
|
||||
lines = [
|
||||
f"# Global Intelligence Feed ({start_date} to {end_date})",
|
||||
f"# Source: Polaris Knowledge API",
|
||||
f"# Briefs: {len(briefs)}",
|
||||
"",
|
||||
]
|
||||
|
||||
for b in briefs:
|
||||
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_sec_filings(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
) -> str:
|
||||
"""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)
|
||||
except Exception as e:
|
||||
return f"Error fetching filings for {symbol}: {e}"
|
||||
|
||||
filings = data.get("filings", [])
|
||||
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
|
||||
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Polaris-Exclusive: Sentiment & Trading Signals
|
||||
# (Complements price/fundamental data from yfinance and Alpha Vantage)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def get_sentiment_score(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
) -> str:
|
||||
"""Get composite trading signal from Polaris.
|
||||
|
||||
Returns a multi-factor score combining:
|
||||
- Sentiment (40% weight)
|
||||
- Momentum (25% weight)
|
||||
- Coverage velocity (20% weight)
|
||||
- Event proximity (15% weight)
|
||||
|
||||
Polaris-exclusive: complements price data from other vendors with intelligence signals.
|
||||
"""
|
||||
cache_key = f"sentiment:{symbol}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
client = _get_client()
|
||||
try:
|
||||
data = client.ticker_score(symbol)
|
||||
except Exception as e:
|
||||
return f"Error fetching sentiment score for {symbol}: {e}"
|
||||
|
||||
components = _safe_get(data, "components", {})
|
||||
sent = _safe_get(components, "sentiment", {})
|
||||
mom = _safe_get(components, "momentum", {})
|
||||
vol = _safe_get(components, "volume", {})
|
||||
evt = _safe_get(components, "events", {})
|
||||
|
||||
lines = [
|
||||
f"# Composite Trading Signal: {symbol.upper()}",
|
||||
f"# Source: Polaris Knowledge API",
|
||||
"",
|
||||
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
|
||||
|
||||
|
||||
def get_sector_analysis(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
) -> str:
|
||||
"""Get competitor intelligence — same-sector peers with live price, RSI, sentiment, and news coverage.
|
||||
|
||||
Polaris-exclusive: complements price data from other vendors with intelligence signals.
|
||||
"""
|
||||
cache_key = f"sector_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 sector analysis for {symbol}: {e}"
|
||||
|
||||
peers = data.get("competitors", [])
|
||||
lines = [
|
||||
f"# Sector & Peer Analysis: {symbol.upper()} ({_safe_get(data, 'sector')})",
|
||||
f"# Source: Polaris Knowledge API",
|
||||
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
|
||||
|
||||
|
||||
def get_news_impact(
|
||||
symbol: Annotated[str, "ticker symbol of the company"],
|
||||
) -> str:
|
||||
"""Measure how news moved the stock price — brief-to-price causation analysis.
|
||||
|
||||
Polaris-exclusive: complements price data from other vendors with intelligence signals.
|
||||
"""
|
||||
cache_key = f"impact:{symbol}"
|
||||
cached = _cached(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
client = _get_client()
|
||||
try:
|
||||
data = client.news_impact(symbol)
|
||||
except Exception as e:
|
||||
return f"Error fetching news impact for {symbol}: {e}"
|
||||
|
||||
best = data.get("best_impact", {}) or {}
|
||||
worst = data.get("worst_impact", {}) or {}
|
||||
|
||||
lines = [
|
||||
f"# News Impact Analysis: {symbol.upper()}",
|
||||
f"# Source: Polaris Knowledge API",
|
||||
"",
|
||||
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')}%",
|
||||
"",
|
||||
]
|
||||
|
||||
if best:
|
||||
lines.append(f"Best Impact: {_safe_get(best, 'headline', '')[:60]} (+{_safe_get(best, 'impact_1d_pct')}%)")
|
||||
if worst:
|
||||
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
|
||||
# (Complements price/fundamental data from yfinance and Alpha Vantage)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
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 {}
|
||||
macd = latest.get("macd", {}) or {}
|
||||
boll = latest.get("bollinger", {}) or {}
|
||||
stoch = latest.get("stochastic", {}) or {}
|
||||
|
||||
lines = [
|
||||
f"# Technical Analysis: {symbol.upper()}",
|
||||
f"# Source: Polaris Knowledge API (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(macd, 'macd')} (signal={_safe_get(macd, 'signal')}, hist={_safe_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(boll, 'upper')}, middle={_safe_get(boll, 'middle')}, lower={_safe_get(boll, 'lower')}",
|
||||
f"ATR(14): {_safe_get(latest, 'atr_14')}",
|
||||
f"Stochastic: K={_safe_get(stoch, 'k')}, D={_safe_get(stoch, '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
|
||||
|
|
@ -25,13 +25,15 @@ DEFAULT_CONFIG = {
|
|||
# Data vendor configuration
|
||||
# Category-level configuration (default for all tools in category)
|
||||
"data_vendors": {
|
||||
"core_stock_apis": "yfinance", # Options: alpha_vantage, yfinance
|
||||
"technical_indicators": "yfinance", # Options: alpha_vantage, yfinance
|
||||
"fundamental_data": "yfinance", # Options: alpha_vantage, yfinance
|
||||
"news_data": "yfinance", # Options: alpha_vantage, yfinance
|
||||
"core_stock_apis": "yfinance", # Options: alpha_vantage, yfinance, polaris
|
||||
"technical_indicators": "yfinance", # Options: alpha_vantage, yfinance, polaris
|
||||
"fundamental_data": "yfinance", # Options: alpha_vantage, yfinance, polaris
|
||||
"news_data": "yfinance", # Options: alpha_vantage, yfinance, polaris
|
||||
"sentiment_analysis": "polaris", # Polaris-exclusive: trading signals, sector analysis, news impact
|
||||
},
|
||||
# Tool-level configuration (takes precedence over category-level)
|
||||
"tool_vendors": {
|
||||
# Example: "get_stock_data": "alpha_vantage", # Override category default
|
||||
# Example: "get_news": "polaris", # Use Polaris for sentiment-scored news
|
||||
},
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue