77 lines
2.4 KiB
Python
77 lines
2.4 KiB
Python
# -*- coding: utf-8 -*-
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# flake8: noqa: E501
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# pylint: disable=C0301
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# Agent configuration for dashboard display
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AGENT_CONFIG = {
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"portfolio_manager": {
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"name": "投资经理",
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"role": "投资经理",
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"avatar": "pm",
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"is_team_role": True,
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},
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"risk_manager": {
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"name": "风控经理",
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"role": "风控经理",
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"avatar": "risk",
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"is_team_role": True,
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},
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"sentiment_analyst": {
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"name": "情绪分析师",
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"role": "情绪分析师",
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"avatar": "sentiment",
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"is_team_role": False,
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},
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"technical_analyst": {
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"name": "技术分析师",
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"role": "技术分析师",
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"avatar": "technical",
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"is_team_role": False,
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},
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"fundamentals_analyst": {
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"name": "基本面分析师",
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"role": "基本面分析师",
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"avatar": "fundamentals",
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"is_team_role": False,
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},
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"valuation_analyst": {
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"name": "估值分析师",
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"role": "估值分析师",
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"avatar": "valuation",
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"is_team_role": False,
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},
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}
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ANALYST_TYPES = {
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"fundamentals_analyst": {
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"display_name": "Fundamentals Analyst",
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"agent_id": "fundamentals_analyst",
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"description": "Uses LLM to intelligently select analysis tools, focuses on financial data and company fundamental analysis",
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"order": 12,
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},
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"technical_analyst": {
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"display_name": "Technical Analyst",
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"agent_id": "technical_analyst",
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"description": "Uses LLM to intelligently select analysis tools, focuses on technical indicators and chart analysis",
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"order": 11,
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},
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"sentiment_analyst": {
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"display_name": "Sentiment Analyst",
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"agent_id": "sentiment_analyst",
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"description": "Uses LLM to intelligently select analysis tools, analyzes market sentiment and news sentiment",
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"order": 13,
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},
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"valuation_analyst": {
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"display_name": "Valuation Analyst",
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"agent_id": "valuation_analyst",
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"description": "Uses LLM to intelligently select analysis tools, focuses on company valuation and value assessment",
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"order": 14,
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},
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# "comprehensive_analyst": {
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# "display_name": "Comprehensive Analyst",
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# "agent_id": "comprehensive_analyst",
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# "description": "Uses LLM to intelligently select analysis tools, performs comprehensive analysis",
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# "order": 15
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# }
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}
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