76 lines
3.4 KiB
Python
76 lines
3.4 KiB
Python
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
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from tradingagents.agents.utils.agent_utils import get_news
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def create_social_media_analyst(llm, config):
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"""Create the social media analyst node with language support."""
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def social_media_analyst_node(state):
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current_date = state["trade_date"]
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ticker = state["company_of_interest"]
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company_name = state["company_of_interest"]
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tools = [
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get_news,
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]
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language = config["output_language"]
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language_prompts = {
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"en": "",
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"zh-tw": "Use Traditional Chinese as the output.",
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"zh-cn": "Use Simplified Chinese as the output.",
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}
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language_prompt = language_prompts.get(language, "")
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system_message = (
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"""
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You are a social media and company-specific news analyst. Your goal is to evaluate the company's public sentiment and perception over the past 7 days.
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Analyze trending social media posts, sentiment dynamics, and relevant company news to identify shifts in market sentiment, brand reputation, and potential investor implications.
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Use the tool get_news(query, start_date, end_date) to gather company-specific social media and news data. Extract qualitative and quantitative trends across sources.
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Your analysis should explain *why* sentiment changes, *who* is influencing discourse (e.g., media, influencers, customers), and *how* it may impact investor behavior.
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Avoid vague summaries such as 'public opinion is mixed'; support claims with examples, sentiment ratios, or trend direction.
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End with a structured Markdown table summarizing key daily sentiment, major social trends, and investment-relevant insights.
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Use objective, professional, and journalistic tone, but focus on financial implications.
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Cite quantitative data where possible, and avoid overly general statements.
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Use the available tools to search for company-specific and global macro news:
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- get_news(query, start_date, end_date) → targeted or company-level analysis
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"""
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)
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prompt = ChatPromptTemplate.from_messages(
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[
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(
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"system",
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f"""
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You are a helpful AI assistant collaborating with other domain experts.
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Use the provided tools to make concrete progress toward the analysis goal.
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If the deliverable includes a final trading stance (BUY/HOLD/SELL), prefix your message clearly with:
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FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL**
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You have access to the following tools: {tools}.
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{system_message}
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Current date: {current_date} | Target company: {ticker}
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Output language: ***{language_prompt}***
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"""
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),
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MessagesPlaceholder(variable_name="messages"),
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]
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)
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chain = prompt | llm.bind_tools(tools)
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result = chain.invoke(state["messages"])
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report = ""
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if len(result.tool_calls) == 0:
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report = result.content
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return {
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"messages": [result],
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"sentiment_report": report,
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}
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return social_media_analyst_node
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