45 lines
1.5 KiB
Python
45 lines
1.5 KiB
Python
# TradingAgents/graph/signal_processing.py
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from langchain_anthropic import ChatAnthropic
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_openai import ChatOpenAI
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class SignalProcessor:
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"""Processes trading signals to extract actionable decisions."""
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def __init__(
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self,
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quick_thinking_llm: ChatOpenAI | ChatAnthropic | ChatGoogleGenerativeAI,
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):
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"""Initialize with an LLM for processing."""
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self.quick_thinking_llm = quick_thinking_llm
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def process_signal(self, full_signal: str) -> str:
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"""
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Process a full trading signal to extract the core decision.
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Args:
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full_signal: Complete trading signal text
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Returns:
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Extracted decision (BUY, SELL, or HOLD)
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"""
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messages = [
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(
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"system",
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"You are an efficient assistant designed to analyze paragraphs or financial reports provided by a group of analysts. Your task is to extract the investment decision: SELL, BUY, or HOLD. Provide only the extracted decision (SELL, BUY, or HOLD) as your output, without adding any additional text or information.",
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),
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("human", full_signal),
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]
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result = self.quick_thinking_llm.invoke(messages).content
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# Ensure we return a string
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if isinstance(result, str):
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return result
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elif isinstance(result, list):
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return str(result)
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else:
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return str(result)
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