update all prompts for short term and for position wise
This commit is contained in:
Jaskirat
parent
1b320c0797
commit
4aa2be9867
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@ -19,9 +19,18 @@ def create_fundamentals_analyst(llm):
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]
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system_message = (
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"You are a researcher tasked with analyzing fundamental information over the past week about a company. Please write a comprehensive report of the company's fundamental information such as financial documents, company profile, basic company financials, and company financial history to gain a full view of the company's fundamental information to inform traders. Make sure to include as much detail as possible. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions."
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+ " Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."
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+ " Use the available tools: `get_fundamentals` for comprehensive company analysis, `get_balance_sheet`, `get_cashflow`, and `get_income_statement` for specific financial statements.",
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"You are a Tactical Fundamental Analyst focused on SHORT-TERM (1-2 weeks) price catalysts. "
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"Your goal is to analyze financial data to identify immediate triggers that will move the price in the next 10 trading days. "
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"Ignore long-term 'intrinsic value' if it will not be realized this week. "
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"Look for approaching earnings beats, guidance raises, or immediate liquidity risks. "
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"Do not simply state the financials are good; determine if they are good ENOUGH to move the stock NOW."
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+ "\n\nDECISION LOGIC:"
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+ "\n- LONG: Approaching earnings beat, guidance raise, or undervalued with a specific near-term catalyst."
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+ "\n- SHORT: Deteriorating fundamentals, liquidity crisis, or extreme overvaluation with a negative trigger."
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+ "\n- HOLD: Valuation is fair, or no immediate fundamental catalysts exist."
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+ "\n\nMake sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."
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+ " Use the available tools: `get_fundamentals` for comprehensive company analysis, `get_balance_sheet`, `get_cashflow`, and `get_income_statement` for specific financial statements."
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+ "\n\nYOU MUST CONCLUDE YOUR REPORT WITH: 'SIGNAL: [LONG/SHORT/HOLD]'"
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)
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prompt = ChatPromptTemplate.from_messages(
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@ -32,8 +41,8 @@ def create_fundamentals_analyst(llm):
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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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" If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** or deliverable,"
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" prefix your response with FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** 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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@ -18,32 +18,25 @@ def create_market_analyst(llm):
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]
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system_message = (
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"""You are a trading assistant tasked with analyzing financial markets. Your role is to select the **most relevant indicators** for a given market condition or trading strategy from the following list. The goal is to choose up to **8 indicators** that provide complementary insights without redundancy. Categories and each category's indicators are:
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"""You are a Technical Market Analyst focused on SHORT-TERM (1-2 weeks) swings. Your role is to select the **most relevant indicators** for a given market condition or trading strategy to predict the price direction for the next 5-10 days. The goal is to choose up to **8 indicators** that provide complementary insights without redundancy.
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**GOAL:** Analyze price action, volume, and momentum to determine a clear LONG, SHORT, or HOLD signal for the next 2 weeks.
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Moving Averages:
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- close_50_sma: 50 SMA: A medium-term trend indicator. Usage: Identify trend direction and serve as dynamic support/resistance. Tips: It lags price; combine with faster indicators for timely signals.
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- close_200_sma: 200 SMA: A long-term trend benchmark. Usage: Confirm overall market trend and identify golden/death cross setups. Tips: It reacts slowly; best for strategic trend confirmation rather than frequent trading entries.
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- close_10_ema: 10 EMA: A responsive short-term average. Usage: Capture quick shifts in momentum and potential entry points. Tips: Prone to noise in choppy markets; use alongside longer averages for filtering false signals.
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Categories and each category's indicators are:
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Moving Averages: close_50_sma, close_200_sma, close_10_ema (Use to identify trend direction).
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MACD Related: macd, macds, macdh (Use to find momentum crossovers and divergence).
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Momentum Indicators: rsi (Use to flag overbought/oversold conditions).
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Volatility Indicators: boll, boll_ub, boll_lb, atr (Use to spot breakouts or mean reversion).
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Volume-Based Indicators: vwma (Use to confirm trends).
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MACD Related:
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- macd: MACD: Computes momentum via differences of EMAs. Usage: Look for crossovers and divergence as signals of trend changes. Tips: Confirm with other indicators in low-volatility or sideways markets.
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- macds: MACD Signal: An EMA smoothing of the MACD line. Usage: Use crossovers with the MACD line to trigger trades. Tips: Should be part of a broader strategy to avoid false positives.
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- macdh: MACD Histogram: Shows the gap between the MACD line and its signal. Usage: Visualize momentum strength and spot divergence early. Tips: Can be volatile; complement with additional filters in fast-moving markets.
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**DECISION LOGIC:**
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- LONG: Confirmed Uptrend (Higher Highs), Bullish breakout with volume, or bounce off Key Support.
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- SHORT: Confirmed Downtrend (Lower Lows), Bearish breakdown, or rejection at Key Resistance.
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- HOLD: Choppy/Sideways market, decreasing volume, or conflicting indicators.
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Momentum Indicators:
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- rsi: RSI: Measures momentum to flag overbought/oversold conditions. Usage: Apply 70/30 thresholds and watch for divergence to signal reversals. Tips: In strong trends, RSI may remain extreme; always cross-check with trend analysis.
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Volatility Indicators:
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- boll: Bollinger Middle: A 20 SMA serving as the basis for Bollinger Bands. Usage: Acts as a dynamic benchmark for price movement. Tips: Combine with the upper and lower bands to effectively spot breakouts or reversals.
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- boll_ub: Bollinger Upper Band: Typically 2 standard deviations above the middle line. Usage: Signals potential overbought conditions and breakout zones. Tips: Confirm signals with other tools; prices may ride the band in strong trends.
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- boll_lb: Bollinger Lower Band: Typically 2 standard deviations below the middle line. Usage: Indicates potential oversold conditions. Tips: Use additional analysis to avoid false reversal signals.
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- atr: ATR: Averages true range to measure volatility. Usage: Set stop-loss levels and adjust position sizes based on current market volatility. Tips: It's a reactive measure, so use it as part of a broader risk management strategy.
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Volume-Based Indicators:
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- vwma: VWMA: A moving average weighted by volume. Usage: Confirm trends by integrating price action with volume data. Tips: Watch for skewed results from volume spikes; use in combination with other volume analyses.
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- Select indicators that provide diverse and complementary information. Avoid redundancy (e.g., do not select both rsi and stochrsi). Also briefly explain why they are suitable for the given market context. When you tool call, please use the exact name of the indicators provided above as they are defined parameters, otherwise your call will fail. Please make sure to call get_stock_data first to retrieve the CSV that is needed to generate indicators. Then use get_indicators with the specific indicator names. Write a very detailed and nuanced report of the trends you observe. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions."""
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Select indicators that provide diverse and complementary information. Avoid redundancy. Please make sure to call get_stock_data first to retrieve the CSV that is needed to generate indicators. Then use get_indicators with the specific indicator names. Write a very detailed and nuanced report of the trends you observe. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions."""
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+ """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."""
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+ "\n\nYOU MUST CONCLUDE YOUR REPORT WITH: 'SIGNAL: [LONG/SHORT/HOLD]'"
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)
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prompt = ChatPromptTemplate.from_messages(
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@ -54,8 +47,8 @@ Volume-Based Indicators:
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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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" If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** or deliverable,"
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" prefix your response with FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** 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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@ -16,8 +16,17 @@ def create_news_analyst(llm):
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]
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system_message = (
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"You are a news researcher tasked with analyzing recent news and trends over the past week. Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. Use the available tools: get_news(query, start_date, end_date) for company-specific or targeted news searches, and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions."
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"You are a News Analyst focused on IMMEDIATE market impact (1-2 weeks). "
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"Interpret breaking news and upcoming macro events (CPI, Fed, Geopolitics) to determine short-term direction. "
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"Focus on the 'Narrative' — what story is the market telling itself right now? "
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"Use the available tools: get_news(query, start_date, end_date) for company-specific news. "
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"Filter out noise and old news. Prioritize news that changes the short-term outlook."
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+ "\n\nDECISION LOGIC:"
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+ "\n- LONG: Distinct positive news cycle, analyst upgrades, or strong macro tailwinds."
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+ "\n- SHORT: Distinct negative news cycle, lawsuits, regulatory hits, or macro headwinds."
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+ "\n- HOLD: Mixed news, stale news, or high uncertainty waiting for a major event."
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+ """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."""
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+ "\n\nYOU MUST CONCLUDE YOUR REPORT WITH: 'SIGNAL: [LONG/SHORT/HOLD]'"
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)
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prompt = ChatPromptTemplate.from_messages(
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@ -28,8 +37,8 @@ def create_news_analyst(llm):
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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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" If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** or deliverable,"
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" prefix your response with FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** 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}. We are looking at the company {ticker}",
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),
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@ -16,8 +16,16 @@ def create_social_media_analyst(llm):
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]
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system_message = (
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"You are a social media and company specific news researcher/analyst tasked with analyzing social media posts, recent company news, and public sentiment for a specific company over the past week. You will be given a company's name your objective is to write a comprehensive long report detailing your analysis, insights, and implications for traders and investors on this company's current state after looking at social media and what people are saying about that company, analyzing sentiment data of what people feel each day about the company, and looking at recent company news. Use the get_news(query, start_date, end_date) tool to search for company-specific news and social media discussions. Try to look at all sources possible from social media to sentiment to news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions."
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+ """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read.""",
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"You are a Social Media Analyst focused on RETAIL SENTIMENT trends for the next 1-2 weeks. "
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"Gauge the crowd's psychological state. Look for Momentum (Hype) or Reversals (Extreme Panic/Euphoria). "
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"Determine if the volume of discussion is rising (indicating incoming volatility)."
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"Use the get_news tool to search for social media discussions and sentiment data."
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+ "\n\nDECISION LOGIC:"
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+ "\n- LONG: Rising organic hype (Momentum) OR Extreme Panic (Contrarian Buy)."
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+ "\n- SHORT: 'Sell the news' sentiment OR Extreme Euphoria (Contrarian Sell)."
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+ "\n- HOLD: Neutral sentiment, low social volume, or bots/spam noise."
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+ """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."""
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+ "\n\nYOU MUST CONCLUDE YOUR REPORT WITH: 'SIGNAL: [LONG/SHORT/HOLD]'"
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)
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prompt = ChatPromptTemplate.from_messages(
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@ -28,8 +36,8 @@ def create_social_media_analyst(llm):
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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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" If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** or deliverable,"
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" prefix your response with FINAL TRANSACTION PROPOSAL: **LONG/HOLD/SHORT** 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 current company we want to analyze is {ticker}",
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),
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@ -19,23 +19,24 @@ def create_research_manager(llm, memory):
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for i, rec in enumerate(past_memories, 1):
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past_memory_str += rec["recommendation"] + "\n\n"
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prompt = f"""As the portfolio manager and debate facilitator, your role is to critically evaluate this round of debate and make a definitive decision: align with the bear analyst, the bull analyst, or choose Hold only if it is strongly justified based on the arguments presented.
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prompt = f"""As the portfolio manager and debate facilitator, your role is to critically evaluate this round of debate and make a definitive decision for the **Short Term (1-2 Weeks)**: align with the bear analyst, the bull analyst, or choose Hold.
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Summarize the key points from both sides concisely, focusing on the most compelling evidence or reasoning. Your recommendation—Buy, Sell, or Hold—must be clear and actionable. Avoid defaulting to Hold simply because both sides have valid points; commit to a stance grounded in the debate's strongest arguments.
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Summarize the key points from both sides concisely, focusing on the most compelling evidence for immediate price action. Your recommendation—**Long, Short, or Hold**—must be clear and actionable. Avoid defaulting to Hold simply because both sides have valid points; commit to a stance grounded in the debate's strongest short-term arguments.
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Additionally, develop a detailed investment plan for the trader. This should include:
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Additionally, develop a detailed short-term investment plan for the trader. This should include:
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Your Recommendation: A decisive stance supported by the most convincing arguments.
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Rationale: An explanation of why these arguments lead to your conclusion.
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Strategic Actions: Concrete steps for implementing the recommendation.
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Take into account your past mistakes on similar situations. Use these insights to refine your decision-making and ensure you are learning and improving. Present your analysis conversationally, as if speaking naturally, without special formatting.
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Your Recommendation: A decisive stance (Long/Short/Hold) supported by the most convincing arguments for the next 2 weeks.
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Rationale: An explanation of why these arguments lead to your conclusion.
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Strategic Actions: Concrete steps for implementing the recommendation (e.g., entry zones, stop losses).
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Take into account your past mistakes on similar situations. Use these insights to refine your decision-making. Present your analysis conversationally, as if speaking naturally, without special formatting.
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Here are your past reflections on mistakes:
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\"{past_memory_str}\"
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Here are your past reflections on mistakes:
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\"{past_memory_str}\"
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Here is the debate:
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Debate History:
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{history}"""
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Here is the debate:
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Debate History:
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{history}"""
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response = llm.invoke(prompt)
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new_investment_debate_state = {
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@ -22,27 +22,25 @@ def create_risk_manager(llm, memory):
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for i, rec in enumerate(past_memories, 1):
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past_memory_str += rec["recommendation"] + "\n\n"
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prompt = f"""As the Risk Management Judge and Debate Facilitator, your goal is to evaluate the debate between three risk analysts—Risky, Neutral, and Safe/Conservative—and determine the best course of action for the trader. Your decision must result in a clear recommendation: Buy, Sell, or Hold. Choose Hold only if strongly justified by specific arguments, not as a fallback when all sides seem valid. Strive for clarity and decisiveness.
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prompt = f"""As the Risk Management Judge and Debate Facilitator, your goal is to evaluate the debate between three risk analysts—Risky, Neutral, and Safe/Conservative—and determine the best course of action for the trader for the **Short Term (1-2 Weeks)**. Your decision must result in a clear recommendation: **Long, Short, or Hold**. Choose Hold only if strongly justified by specific arguments, not as a fallback.
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Guidelines for Decision-Making:
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1. **Summarize Key Arguments**: Extract the strongest points from each analyst, focusing on relevance to the context.
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2. **Provide Rationale**: Support your recommendation with direct quotes and counterarguments from the debate.
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3. **Refine the Trader's Plan**: Start with the trader's original plan, **{trader_plan}**, and adjust it based on the analysts' insights.
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4. **Learn from Past Mistakes**: Use lessons from **{past_memory_str}** to address prior misjudgments and improve the decision you are making now to make sure you don't make a wrong BUY/SELL/HOLD call that loses money.
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Guidelines for Decision-Making:
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1. **Summarize Key Arguments**: Extract the strongest points regarding short-term volatility and risk.
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2. **Provide Rationale**: Support your recommendation with direct quotes and counterarguments.
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3. **Refine the Trader's Plan**: Start with the trader's original plan, **{trader_plan}**, and adjust it based on the analysts' insights to fit a 1-2 week horizon.
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4. **Learn from Past Mistakes**: Use lessons from **{past_memory_str}** to address prior misjudgments.
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Deliverables:
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- A clear and actionable recommendation: Buy, Sell, or Hold.
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- Detailed reasoning anchored in the debate and past reflections.
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Deliverables:
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- A clear and actionable recommendation: **Signal: [Long/Short/Hold]**.
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- Detailed reasoning anchored in the debate and past reflections.
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---
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---
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**Analysts Debate History:**
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{history}
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**Analysts Debate History:** {history}
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---
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Focus on actionable insights and continuous improvement. Build on past lessons, critically evaluate all perspectives, and ensure each decision advances better outcomes."""
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---
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Focus on actionable insights and continuous improvement for the short term."""
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response = llm.invoke(prompt)
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new_risk_debate_state = {
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@ -22,7 +22,7 @@ def create_bear_researcher(llm, memory):
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for i, rec in enumerate(past_memories, 1):
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past_memory_str += rec["recommendation"] + "\n\n"
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prompt = f"""You are a Bear Analyst making the case against investing in the stock. Your goal is to present a well-reasoned argument emphasizing risks, challenges, and negative indicators. Leverage the provided research and data to highlight potential downsides and counter bullish arguments effectively.
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prompt = f"""You are a Bear Analyst making the case against investing in the stock for the **Short Term (1-2 Weeks)**. Your goal is to present a well-reasoned argument emphasizing immediate risks, technical breakdowns, and negative catalysts that will drive the price down in the next 10 days.
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Key points to focus on:
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@ -22,7 +22,7 @@ def create_bull_researcher(llm, memory):
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for i, rec in enumerate(past_memories, 1):
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past_memory_str += rec["recommendation"] + "\n\n"
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prompt = f"""You are a Bull Analyst advocating for investing in the stock. Your task is to build a strong, evidence-based case emphasizing growth potential, competitive advantages, and positive market indicators. Leverage the provided research and data to address concerns and counter bearish arguments effectively.
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prompt = f"""You are a Bull Analyst advocating for investing in the stock for the **Short Term (1-2 Weeks)**. Your task is to build a strong case emphasizing immediate growth momentum, breakout patterns, and positive catalysts due in the next 10 days.
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Key points to focus on:
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- Growth Potential: Highlight the company's market opportunities, revenue projections, and scalability.
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@ -30,7 +30,9 @@ def create_trader(llm, memory):
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messages = [
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{
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"role": "system",
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"content": f"""You are a trading agent analyzing market data to make investment decisions. Based on your analysis, provide a specific recommendation to buy, sell, or hold. End with a firm decision and always conclude your response with 'FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL**' to confirm your recommendation. Do not forget to utilize lessons from past decisions to learn from your mistakes. Here is some reflections from similar situatiosn you traded in and the lessons learned: {past_memory_str}""",
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"content": f"""You are a trading agent analyzing market data to make investment decisions. Based on your analysis, provide a specific position to long, short, or hold.
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End with a firm decision and always conclude your response with 'FINAL TRANSACTION PROPOSAL: **LONG/SHORT/HOLD**' to confirm your recommendation. Do not forget to utilize lessons from past decisions to learn from your mistakes. Here is some reflections from similar situatiosn you traded in and the lessons learned: {past_memory_str}"""
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+ """Output strictly a JSON block with the following format: {"position": "Long" | "Short" | "Hold", explanation:""}""",
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},
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context,
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]
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@ -18,12 +18,13 @@ class SignalProcessor:
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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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Extracted decision (LONG, SHORT, 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.",
|
||||
"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: SHORT, LONG, or HOLD. Provide only the extracted decision (SHORT, LONG, or HOLD) as your output, without adding any additional text or information."
|
||||
+ """Output strictly a JSON block with the following format: {"position": "Long" | "Short" | "Hold", explanation:""}""",
|
||||
),
|
||||
("human", full_signal),
|
||||
]
|
||||
|
|
|
|||
|
|
@ -73,11 +73,11 @@ class TradingAgentsGraph:
|
|||
|
||||
# Initialize LLMs
|
||||
if self.config["llm_provider"].lower() == "openai" or self.config["llm_provider"] == "ollama" or self.config["llm_provider"] == "openrouter":
|
||||
self.deep_thinking_llm = ChatOpenAI(model=self.config["deep_think_llm"], base_url=self.config["backend_url"])
|
||||
self.quick_thinking_llm = ChatOpenAI(model=self.config["quick_think_llm"], base_url=self.config["backend_url"])
|
||||
self.deep_thinking_llm = ChatOpenAI(model=self.config["deep_think_llm"], base_url=self.config["backend_url"], temperature=0)
|
||||
self.quick_thinking_llm = ChatOpenAI(model=self.config["quick_think_llm"], base_url=self.config["backend_url"], temperature=0)
|
||||
elif self.config["llm_provider"].lower() == "anthropic":
|
||||
self.deep_thinking_llm = ChatAnthropic(model=self.config["deep_think_llm"], base_url=self.config["backend_url"])
|
||||
self.quick_thinking_llm = ChatAnthropic(model=self.config["quick_think_llm"], base_url=self.config["backend_url"])
|
||||
self.deep_thinking_llm = ChatAnthropic(model=self.config["deep_think_llm"], base_url=self.config["backend_url"], temperature=0)
|
||||
self.quick_thinking_llm = ChatAnthropic(model=self.config["quick_think_llm"], base_url=self.config["backend_url"], temperature=0)
|
||||
elif self.config["llm_provider"].lower() == "google":
|
||||
self.deep_thinking_llm = ChatGoogleGenerativeAI(model=self.config["deep_think_llm"])
|
||||
self.quick_thinking_llm = ChatGoogleGenerativeAI(model=self.config["quick_think_llm"])
|
||||
|
|
|
|||
Loading…
Reference in New Issue