23 lines
926 B
Python
23 lines
926 B
Python
from tradingagents.graph.trading_graph import TradingAgentsGraph
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from tradingagents.default_config import DEFAULT_CONFIG
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# Create a custom config
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config = DEFAULT_CONFIG.copy()
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config["llm_provider"] = "ollama" # Use a different model
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config["backend_url"] = "http://localhost:11434" # Use a different backend
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config["deep_think_llm"] = "mixtral:8x7b-instruct-v0.1-q4_K_M" # Use a different model
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config["quick_think_llm"] = "phi3:mini" # Use a different model
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config["embedding_model"] = "fingpt:7b" # Use a different embedding model
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config["max_debate_rounds"] = 1 # Increase debate rounds
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config["online_tools"] = True # Increase debate rounds
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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", "2025-07-07")
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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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