creat

Signed-off-by: TIANHE <TIANHE@GMAIL.COM>
2025-12-29 03:06:49 +08:00
commit f43312a858
292 changed files with 103739 additions and 0 deletions
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+"""
+Trader agent.
+Synthesizes all analysis outputs and produces a final trading decision.
+"""
+import json
+from typing import Dict, Any
+from .base_agent import BaseAgent
+from app.services.llm import LLMService
+
+logger = __import__('app.utils.logger', fromlist=['get_logger']).get_logger(__name__)
+
+
+class TraderAgent(BaseAgent):
+    """Trader agent."""
+    
+    def __init__(self, memory=None):
+        super().__init__("TraderAgent", memory)
+        self.llm_service = LLMService()
+    
+    def analyze(self, context: Dict[str, Any]) -> Dict[str, Any]:
+        """Make a final trading decision."""
+        market = context.get('market')
+        symbol = context.get('symbol')
+        language = context.get('language', 'zh-CN')
+        model = context.get('model')
+        
+        # Inputs
+        market_report = context.get('market_report', {})
+        fundamental_report = context.get('fundamental_report', {})
+        news_report = context.get('news_report', {})
+        sentiment_report = context.get('sentiment_report', {})
+        risk_report = context.get('risk_report', {})
+        
+        # Debate outputs
+        bull_argument = context.get('bull_argument', {})
+        bear_argument = context.get('bear_argument', {})
+        research_decision = context.get('research_decision', '')
+        
+        # Memory
+        situation = f"{market}:{symbol} trading decision"
+        memories = self.get_memories(situation, n_matches=2)
+        memory_prompt = self.format_memories_for_prompt(memories)
+        
+        lang_instruction = self._get_language_instruction(language)
+        system_prompt = f"""You are a Trader, needing to make a final trading decision based on all analysis results.
+{lang_instruction}
+
+Your tasks:
+1. Synthesize analysis results from all dimensions.
+2. Consider both bullish and bearish arguments.
+3. Make a clear trading decision: BUY, SELL, or HOLD.
+4. Provide a detailed trading plan.
+5. Learn from historical experience: {memory_prompt}
+6. **Confidence Score**: Evaluate your confidence in the decision (0-100). Be realistic. If the signals are mixed, confidence should be lower (e.g., 40-60). Only use high confidence (>80) for very clear strong signals. Do NOT default to 85.
+
+Please return in JSON format as follows:
+{{
+  "decision": "BUY/SELL/HOLD",
+  "confidence": 85,
+  "reasoning": "Reason for decision...",
+  "trading_plan": {{
+    "entry_price": "Suggested entry price",
+    "stop_loss": "Stop loss price",
+    "take_profit": "Take profit price",
+    "position_size": "Suggested position size"
+  }},
+  "report": "Detailed trading plan report..."
+}}"""
+
+        user_prompt = f"""Based on all the following analyses, make a trading decision for {symbol} in {market} market:
+
+**Market Technical Analysis:**
+{json.dumps(market_report.get('data', {}), ensure_ascii=False, indent=2) if market_report else 'No Data'}
+
+**Fundamental Analysis:**
+{json.dumps(fundamental_report.get('data', {}), ensure_ascii=False, indent=2) if fundamental_report else 'No Data'}
+
+**News Analysis:**
+{json.dumps(news_report.get('data', {}), ensure_ascii=False, indent=2) if news_report else 'No Data'}
+
+**Sentiment Analysis:**
+{json.dumps(sentiment_report.get('data', {}), ensure_ascii=False, indent=2) if sentiment_report else 'No Data'}
+
+**Risk Analysis:**
+{json.dumps(risk_report.get('data', {}), ensure_ascii=False, indent=2) if risk_report else 'No Data'}
+
+**Bullish Argument:**
+{json.dumps(bull_argument.get('data', {}), ensure_ascii=False, indent=2) if bull_argument else 'No Data'}
+
+**Bearish Argument:**
+{json.dumps(bear_argument.get('data', {}), ensure_ascii=False, indent=2) if bear_argument else 'No Data'}
+
+**Research Manager Decision:**
+{research_decision if research_decision else 'No Data'}
+
+Please make a clear trading decision (BUY/SELL/HOLD) and provide a detailed trading plan."""
+
+        result = self.llm_service.safe_call_llm(
+            system_prompt,
+            user_prompt,
+            {
+                "decision": "HOLD",
+                "confidence": 50,
+                "reasoning": "",
+                "trading_plan": {},
+                "report": "Failed to parse trader decision"
+            },
+            model=model
+        )
+        
+        return {
+            "type": "trader",
+            "data": result
+        }
+    
+    def _get_language_instruction(self, language: str) -> str:
+        language_map = {
+            'zh-CN': 'Answer in Simplified Chinese.',
+            'zh-TW': 'Answer in Traditional Chinese.',
+            'en-US': 'Answer in English.',
+            'ja-JP': 'Answer in Japanese.',
+            'ko-KR': 'Answer in Korean.',
+            'vi-VN': 'Answer in Vietnamese.',
+            'th-TH': 'Answer in Thai.',
+            'ar-SA': 'Answer in Arabic.',
+            'fr-FR': 'Answer in French.',
+            'de-DE': 'Answer in German.'
+        }
+        return language_map.get(language, 'Answer in English.')