38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
# TradingAgents/graph/signal_processing.py
|
|
|
|
from typing import Union
|
|
from langchain_openai import ChatOpenAI
|
|
from langchain_anthropic import ChatAnthropic
|
|
from langchain_google_genai import ChatGoogleGenerativeAI
|
|
|
|
# Type alias for supported LLM types
|
|
LLMType = Union[ChatOpenAI, ChatAnthropic, ChatGoogleGenerativeAI]
|
|
|
|
|
|
class SignalProcessor:
|
|
"""Processes trading signals to extract actionable decisions."""
|
|
|
|
def __init__(self, quick_thinking_llm: LLMType):
|
|
"""Initialize with an LLM for processing."""
|
|
self.quick_thinking_llm = quick_thinking_llm
|
|
|
|
def process_signal(self, full_signal: str) -> str:
|
|
"""
|
|
Process a full trading signal to extract the core decision.
|
|
|
|
Args:
|
|
full_signal: Complete trading signal text
|
|
|
|
Returns:
|
|
Extracted decision (BUY, SELL, or HOLD)
|
|
"""
|
|
messages = [
|
|
(
|
|
"system",
|
|
"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.",
|
|
),
|
|
("human", full_signal),
|
|
]
|
|
|
|
return str(self.quick_thinking_llm.invoke(messages).content)
|