267 lines
13 KiB
Python
267 lines
13 KiB
Python
import requests
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from typing import Annotated, List
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from tradingagents.config import settings
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# This is for single indicator, unused for now but kept for reference
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def get_crypto_stats_indicators_window(
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symbol: Annotated[str, "ticker symbol of the coin/asset"],
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indicator: Annotated[str, "technical indicator to get the analysis and report of"],
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curr_date: Annotated[
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str, "The current trading date you are trading on, YYYY-mm-dd"
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],
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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 indicator data from TAAPI.io for a given symbol.
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Args:
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symbol: Ticker symbol of the coin/asset (e.g., 'BTC/USDT')
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indicator: Technical indicator to get the analysis and report of (e.g., 'rsi', 'macd', 'sma', 'bbands', 'atr')
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curr_date: The current trading date you are trading on, in YYYY-MM-DD format
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look_back_days: How many days to look back
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Returns:
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str: A formatted report containing the technical indicators for the specified ticker symbol and indicator.
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"""
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# Supported indicators mapping
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supported_indicators = {
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"sma": "Simple Moving Average",
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"macd": "MACD (Moving Average Convergence Divergence)",
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"rsi": "Relative Strength Index",
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"bbands": "Bollinger Bands",
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"atr": "Average True Range"
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}
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# Detailed indicator descriptions and usage
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indicator_descriptions = {
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"sma": "SMA (Simple Moving Average): A basic trend-following indicator that smooths out price data. Usage: Identify trend direction and serve as dynamic support/resistance levels. Tips: Use multiple SMAs for crossover signals; combines well with volume analysis for confirmation.",
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"macd": "MACD: Measures momentum via differences between fast and slow EMAs. Usage: Look for signal line crossovers, centerline crossovers, and divergence patterns for trend changes. Tips: Most effective in trending markets; combine with RSI to avoid false signals in sideways markets.",
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"rsi": "RSI: Oscillator measuring momentum to identify overbought (>70) and oversold (<30) conditions. Usage: Look for reversal signals at extreme levels and divergence with price action. Tips: In strong trends, RSI can remain extreme for extended periods; always confirm with trend analysis.",
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"bbands": "Bollinger Bands: Volatility indicator consisting of upper, middle (SMA), and lower bands based on standard deviations. Usage: Identify overbought/oversold conditions, volatility expansion/contraction, and potential breakout zones. Tips: Price touching bands doesn't guarantee reversal; use band squeeze for volatility breakout trades.",
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"atr": "ATR: Measures market volatility by calculating the average of true ranges over a period. Usage: Set stop-loss levels, position sizing, and identify high/low volatility periods for strategy adjustment. Tips: Higher ATR indicates more volatile conditions; use for risk management rather than directional signals."
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}
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# Validate indicator
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if indicator.lower() not in supported_indicators:
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return f"Error: Indicator '{indicator}' is not supported. Please choose from: {list(supported_indicators.keys())}"
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base_url = settings.TAAPI_BASE_URL
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api_key = settings.TAAPI_API_KEY
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if not api_key:
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return "Error: TAAPI_API_KEY is not set in the configuration."
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# Set backtrack as requested
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backtrack = look_back_days
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# Construct the API URL
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url = f"{base_url}/{indicator.lower()}"
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# Set up parameters for the API call
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params = {
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"secret": api_key,
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"exchange": "binance", # Default to binance exchange for crypto
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"symbol": symbol,
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"interval": "1d", # Daily interval
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"backtrack": backtrack
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}
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try:
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# Make the API request
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response = requests.get(url, params=params)
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response.raise_for_status() # Raise an exception for bad status codes
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# Get the JSON response
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data = response.json()
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# Format the response based on indicator type
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if isinstance(data, list):
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# Handle historical data (multiple periods)
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result_str = f"## {supported_indicators[indicator.lower()]} ({indicator.upper()}) for {symbol}:\n\n"
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for i, period_data in enumerate(data):
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if isinstance(period_data, dict):
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result_str += f"Period {i + 1}:\n"
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for key, value in period_data.items():
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clean_key = key.replace("value", "").replace("Value", "")
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if isinstance(value, (int, float)):
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result_str += f" {clean_key}: {value:.4f}\n"
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else:
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result_str += f" {clean_key}: {value}\n"
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result_str += "\n"
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elif isinstance(data, dict):
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# Handle single period data
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result_str = f"## {supported_indicators[indicator.lower()]} ({indicator.upper()}) for {symbol}:\n\n"
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result_str += f"Current Date: {curr_date}\n"
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result_str += f"Lookback Days: {look_back_days}\n\n"
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# Generic formatting for all indicators
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for key, value in data.items():
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clean_key = key.replace("value", "").replace("Value", "")
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if isinstance(value, (int, float)):
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result_str += f"{clean_key}: {value:.4f}\n"
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else:
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result_str += f"{clean_key}: {value}\n"
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else:
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result_str = f"## {supported_indicators[indicator.lower()]} for {symbol}:\n{str(data)}"
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# Add the indicator description
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result_str += f"\n\n{indicator_descriptions.get(indicator.lower(), 'No description available.')}"
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return result_str
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except requests.exceptions.RequestException as e:
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return f"Error fetching data from TAAPI.io: {str(e)}"
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except ValueError as e:
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return f"Error parsing response from TAAPI.io: {str(e)}"
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except KeyError as e:
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return f"Error: Missing expected field in API response: {str(e)}"
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except Exception as e:
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return f"Unexpected error: {str(e)}"
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def get_crypto_stats_indicators(
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symbol: Annotated[str, "ticker symbol of the coin/asset"],
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indicators: Annotated[List[str], "list of technical indicators to get analysis for"],
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curr_date: Annotated[
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str, "The current trading date you are trading on, YYYY-mm-dd"
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],
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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 multiple technical indicator data from TAAPI.io for a given symbol using bulk API.
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Args:
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symbol: Ticker symbol of the coin/asset (e.g., 'BTC/USDT')
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indicators: List of technical indicators to get analysis for (e.g., ['rsi', 'macd', 'sma', 'bbands', 'atr'])
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curr_date: The current trading date you are trading on, in YYYY-MM-DD format
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look_back_days: How many days to look back
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Returns:
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str: A formatted report containing all requested technical indicators for the specified ticker symbol.
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"""
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# validate symbol it must in format BASE/QUOTE
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if "/" not in symbol:
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return f"Error: Symbol '{symbol}' is not in the correct format. Please use 'BASE/QUOTE' format, e.g., 'BTC/USDT'."
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# Supported indicators mapping
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supported_indicators = {
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"sma": "Simple Moving Average",
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"ema": "Exponential Moving Average",
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"macd": "MACD (Moving Average Convergence Divergence)",
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"rsi": "Relative Strength Index",
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"bbands": "Bollinger Bands",
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"atr": "Average True Range",
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"kdj": "KDJ (Stochastic KDJ)"
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}
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# Detailed indicator descriptions and usage
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indicator_descriptions = {
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"sma": "SMA (Simple Moving Average): A basic trend-following indicator that smooths out price data. Usage: Identify trend direction and serve as dynamic support/resistance levels. Tips: Use multiple SMAs for crossover signals; combines well with volume analysis for confirmation.",
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"ema": "EMA (Exponential Moving Average): A trend-following indicator that gives more weight to recent prices. Usage: More responsive than SMA for trend changes and crossover signals. Tips: Better for short-term trading; reacts faster to price changes than SMA.",
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"macd": "MACD: Measures momentum via differences between fast and slow EMAs. Usage: Look for signal line crossovers, centerline crossovers, and divergence patterns for trend changes. Tips: Most effective in trending markets; combine with RSI to avoid false signals in sideways markets.",
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"rsi": "RSI: Oscillator measuring momentum to identify overbought (>70) and oversold (<30) conditions. Usage: Look for reversal signals at extreme levels and divergence with price action. Tips: In strong trends, RSI can remain extreme for extended periods; always confirm with trend analysis.",
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"bbands": "Bollinger Bands: Volatility indicator consisting of upper, middle (SMA), and lower bands based on standard deviations. Usage: Identify overbought/oversold conditions, volatility expansion/contraction, and potential breakout zones. Tips: Price touching bands doesn't guarantee reversal; use band squeeze for volatility breakout trades.",
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"atr": "ATR: Measures market volatility by calculating the average of true ranges over a period. Usage: Set stop-loss levels, position sizing, and identify high/low volatility periods for strategy adjustment. Tips: Higher ATR indicates more volatile conditions; use for risk management rather than directional signals.",
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"kdj": "KDJ: Advanced stochastic oscillator with three lines (K, D, J). Usage: Identify overbought/oversold conditions and momentum changes. Tips: J line is most sensitive; use crossovers between K, D, and J lines for entry/exit signals."
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}
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# Validate indicators
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invalid_indicators = [ind for ind in indicators if ind.lower() not in supported_indicators]
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if invalid_indicators:
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return f"Error: Indicators {invalid_indicators} are not supported. Please choose from: {list(supported_indicators.keys())}"
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base_url = settings.TAAPI_BASE_URL
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api_key = settings.TAAPI_API_KEY
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if not api_key:
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return "Error: TAAPI_API_KEY is not set in the configuration."
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# Construct the bulk API URL
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url = f"{base_url}/bulk"
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# Prepare indicators list for the bulk request
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indicator_list = []
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for indicator in indicators:
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indicator_list.append({
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"indicator": indicator.lower(),
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"backtrack": look_back_days
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})
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# Set up the JSON payload for the bulk request
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payload = {
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"secret": api_key,
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"construct": {
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"exchange": "binance",
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"symbol": symbol,
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"interval": "1d",
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"indicators": indicator_list
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}
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}
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try:
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# Make the POST request to bulk API
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response = requests.post(url, json=payload)
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response.raise_for_status()
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# Get the JSON response
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data = response.json()
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# Format the bulk response
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result_str = f"# Technical Indicators Report for {symbol}\n\n"
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result_str += f"**Current Date:** {curr_date}\n"
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result_str += f"**Lookback Days:** {look_back_days}\n\n"
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if "data" in data and isinstance(data["data"], list):
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for item in data["data"]:
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if "errors" in item and item["errors"]:
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# Handle errors for individual indicators
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result_str += f"## ❌ Error for {item.get('indicator', 'Unknown').upper()}:\n"
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result_str += f"- {'; '.join(item['errors'])}\n\n"
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continue
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indicator_name = item.get("indicator", "unknown")
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indicator_display = supported_indicators.get(indicator_name, indicator_name.upper())
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result_str += f"## {indicator_display} ({indicator_name.upper()})\n\n"
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# Handle the result data
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if "result" in item and isinstance(item["result"], dict):
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result_data = item["result"]
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# Format the values
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for key, value in result_data.items():
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clean_key = key.replace("value", "").replace("Value", "")
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if clean_key == "":
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clean_key = "Value"
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if isinstance(value, (int, float)):
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result_str += f"**{clean_key}:** {value:.4f}\n"
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else:
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result_str += f"**{clean_key}:** {value}\n"
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# Add description
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if indicator_name in indicator_descriptions:
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result_str += f"\n*{indicator_descriptions[indicator_name]}*\n"
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result_str += "\n---\n\n"
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else:
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result_str += f"Unexpected response format: {str(data)}"
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return result_str
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except requests.exceptions.RequestException as e:
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return f"Error fetching bulk data from TAAPI.io: {str(e)}"
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except ValueError as e:
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return f"Error parsing bulk response from TAAPI.io: {str(e)}"
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except KeyError as e:
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return f"Error: Missing expected field in bulk API response: {str(e)}"
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except Exception as e:
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return f"Unexpected error in bulk request: {str(e)}"
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