42 lines
1.6 KiB
Python
42 lines
1.6 KiB
Python
from tradingagents.graph.trading_graph import TradingAgentsGraph
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from tradingagents.default_config import DEFAULT_CONFIG
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from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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# Create a custom config
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config = DEFAULT_CONFIG.copy()
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config["llm_provider"] = "anthropic"
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config["deep_think_llm"] = "claude-sonnet-4-20250514"
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config["quick_think_llm"] = "claude-sonnet-4-20250514"
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config["backend_url"] = "https://api.anthropic.com"
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config["max_debate_rounds"] = 1 # debate rounds
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# Example: OpenRouter configuration (uncomment to use)
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# config["llm_provider"] = "openrouter"
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# config["deep_think_llm"] = "anthropic/claude-sonnet-4.5" # or any OpenRouter model
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# config["quick_think_llm"] = "anthropic/claude-sonnet-4.5"
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# config["backend_url"] = "https://openrouter.ai/api/v1"
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# Note: Set OPENROUTER_API_KEY in .env file
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# Note: For embeddings, also set OPENAI_API_KEY (OpenRouter doesn't provide embeddings)
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# Configure data vendors (default uses yfinance and alpha_vantage)
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config["data_vendors"] = {
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"core_stock_apis": "yfinance", # Options: yfinance, alpha_vantage, local
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"technical_indicators": "yfinance", # Options: yfinance, alpha_vantage, local
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"fundamental_data": "yfinance", # Options: openai, alpha_vantage, yfinance, local
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"news_data": "google", # Options: openai, alpha_vantage, google, local
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}
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# Initialize with custom config
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ta = TradingAgentsGraph(debug=True, config=config)
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# forward propagate
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_, decision = ta.propagate("NVDA", "2024-05-10")
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print(decision)
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# Memorize mistakes and reflect
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# ta.reflect_and_remember(1000) # parameter is the position returns
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