78 lines
3.3 KiB
Python
78 lines
3.3 KiB
Python
# -*- coding: utf-8 -*-
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import functools
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import time
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import json
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from tradingagents.agents.utils.prompts import get_trader_prompt
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def create_trader(llm, memory, language: str = "zh-TW"):
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"""
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建立一個交易員節點。
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Args:
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llm: 用於生成決策的語言模型。
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memory: 儲存過去情況和反思的記憶體物件。
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language: 報告語言 ('en' 或 'zh-TW')
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Returns:
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function: 一個代表交易員節點的函式。
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"""
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def trader_node(state, name):
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"""交易員節點的執行函式。"""
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company_name = state["company_of_interest"]
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investment_plan = state["investment_plan"]
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market_research_report = state["market_report"]
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sentiment_report = state["sentiment_report"]
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news_report = state["news_report"]
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fundamentals_report = state["fundamentals_report"]
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curr_situation = f"{market_research_report}\n\n{sentiment_report}\n\n{news_report}\n\n{fundamentals_report}"
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past_memories = memory.get_memories(curr_situation, n_matches=2)
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past_memory_str = ""
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if past_memories:
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for i, rec in enumerate(past_memories, 1):
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recommendation = rec["recommendation"]
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past_memory_str += recommendation + "\n\n"
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else:
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past_memory_str = "No past memories found." if language == "en" else "找不到過去的記憶。"
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# Get language-specific prompt
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base_prompt = get_trader_prompt(language)
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if language == "en":
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prompt = f"""{base_prompt}
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【Available Information】
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- Investment Plan: {investment_plan}
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- Past Reflections: {past_memory_str}
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**IMPORTANT**: End your response with "Final Trading Proposal: **Buy/Hold/Sell**"!"""
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system_msg = f"""You are a trading agent analyzing market data to make investment decisions. Based on your analysis, provide specific Buy, Sell, or Hold recommendations. End with a firm decision by always ending your response with "Final Trading Proposal: **Buy/Hold/Sell**" to confirm your recommendation. Don't forget to leverage lessons from past decisions to learn from mistakes. Here are some reflections from similar situations: {past_memory_str}"""
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else:
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prompt = f"""{base_prompt}
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【可用資訊】
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- 投資計畫：{investment_plan}
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- 過去反思：{past_memory_str}
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**重要**：請以「最終交易提案：**買入/持有/賣出**」結束回應！"""
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system_msg = f"""您是一位分析市場數據以做出投資決策的交易代理。根據您的分析，提供具體的買入、賣出或持有建議。以堅定的決策結束，並始終以「最終交易提案：**買入/持有/賣出**」來結束您的回應，以確認您的建議。不要忘記利用過去決策的教訓來從錯誤中學習。以下是您在類似情況下交易的一些反思：{past_memory_str}"""
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messages = [
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{"role": "system", "content": system_msg},
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{"role": "user", "content": prompt},
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]
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result = llm.invoke(messages)
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return {
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"messages": [result],
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"trader_investment_plan": result.content,
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"sender": name,
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}
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return functools.partial(trader_node, name="Trader") |