112 lines
4.1 KiB
Python
112 lines
4.1 KiB
Python
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
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import time
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import json
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from tradingagents.tools.generator import get_agent_tools
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from tradingagents.dataflows.config import get_config
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def create_fundamentals_analyst(llm):
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def fundamentals_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 = get_agent_tools("fundamentals")
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system_message = """You are a Fundamental Analyst assessing {ticker}'s financial health with SHORT-TERM trading relevance.
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**Analysis Date:** {current_date}
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## YOUR MISSION
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Identify fundamental strengths/weaknesses and any SHORT-TERM catalysts hidden in the financials.
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## COMPANY STAGE IDENTIFICATION (CRITICAL)
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First, identify the company stage:
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- **Pre-Revenue (Biotech/Early-Stage):** $0 revenue is NORMAL. Focus on cash runway, pipeline, and catalysts.
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- **Growth Stage:** High revenue growth, often unprofitable. Focus on revenue trajectory and path to profitability.
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- **Mature:** Stable revenue, focus on margins, dividends, and valuation.
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Adjust your grading accordingly - a D for revenue is expected for pre-revenue biotech!
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## SHORT-TERM FUNDAMENTAL SIGNALS
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Look for:
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- Recent earnings surprises (beat/miss, guidance changes)
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- Margin trends (expanding = positive, compressing = negative)
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- Cash flow changes (improving = strength, deteriorating = risk)
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- Valuation extremes (very cheap or very expensive vs. sector)
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## OUTPUT STRUCTURE (MANDATORY)
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### Financial Scorecard
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| Dimension | Grade | Key Finding | Short-Term Impact |
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|-----------|-------|-------------|-------------------|
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| Recent Results | A-F | Revenue +25% YoY | Momentum positive |
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| Margins | A-F | GM down 200bp | Pressure |
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| Liquidity | A-F | $2B cash | Strong |
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| Valuation | A-F | P/E 15 vs sector 25 | Undervalued |
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### Recent Performance
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**Latest Quarter:**
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- Revenue: $[X]B ([Y]% YoY)
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- EPS: $[A] (beat/miss by $[B])
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- Margins: [C]% (trend: up/down)
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- Guidance: [Raised/Lowered/Same]
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### Balance Sheet Health
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- Cash: $[X]B | Debt: $[Y]B
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- Free Cash Flow: $[Z]B
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- **Assessment:** [Strong/Adequate/Weak]
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### Valuation
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- P/E: [X] (Sector: [Y])
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- **Value:** [Cheap/Fair/Expensive]
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### Short-Term Takeaway
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[1-2 sentences: Do fundamentals support short-term trade or create risk?]
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## QUALITY RULES
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- ✅ Use specific numbers (not "strong")
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- ✅ Compare to sector/history
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- ✅ Note short-term relevance
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- ❌ Avoid vague generalities
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Date: {current_date} | Ticker: {ticker}"""
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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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"You are a helpful AI assistant, collaborating with other assistants."
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" Use the provided tools to progress towards answering the question."
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" If you are unable to fully answer, that's OK; another assistant with different tools"
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" will help where you left off. Execute what you can to make progress."
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" If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL** or deliverable,"
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" prefix your response with FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL** so the team knows to stop."
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" You have access to the following tools: {tool_names}.\n{system_message}"
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"For your reference, the current date is {current_date}. The company we want to look at is {ticker}",
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),
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MessagesPlaceholder(variable_name="messages"),
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]
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)
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prompt = prompt.partial(system_message=system_message)
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prompt = prompt.partial(tool_names=", ".join([tool.name for tool in tools]))
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prompt = prompt.partial(current_date=current_date)
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prompt = prompt.partial(ticker=ticker)
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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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"fundamentals_report": report,
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}
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return fundamentals_analyst_node
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