feat: 微服务架构拆分和前后端优化
后端: - 拆分出 agent_service, runtime_service, trading_service, news_service - Gateway 模块化拆分 (gateway_*.py) - 添加 domains/ 领域层 - 新增 control_client, runtime_client - 更新 start-dev.sh 支持 split 服务模式 前端: - 完善 API 服务层 (newsApi, tradingApi) - 更新 vite.config.js - Explain 组件优化 测试: - 添加多个服务 app 测试 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -11,7 +11,7 @@ import pandas as pd
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import yfinance as yf
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from backend.config.data_config import DataSource, get_data_sources
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from backend.data.schema import (
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from shared.schema import (
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CompanyFactsResponse,
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CompanyNews,
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CompanyNewsResponse,
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@@ -1,194 +1,50 @@
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# -*- coding: utf-8 -*-
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from pydantic import BaseModel
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"""Compatibility schema bridge.
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This module preserves the legacy ``backend.data.schema`` import path while
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delegating the actual schema definitions to ``shared.schema``. Keeping one
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canonical DTO set avoids drift as the monolith is split into service-specific
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packages.
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"""
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class Price(BaseModel):
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open: float
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close: float
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high: float
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low: float
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volume: int
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time: str
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from shared.schema import (
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AgentStateData,
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AgentStateMetadata,
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AnalystSignal,
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CompanyFacts,
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CompanyFactsResponse,
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CompanyNews,
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CompanyNewsResponse,
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FinancialMetrics,
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FinancialMetricsResponse,
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InsiderTrade,
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InsiderTradeResponse,
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LineItem,
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LineItemResponse,
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Portfolio,
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Position,
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Price,
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PriceResponse,
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TickerAnalysis,
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)
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class PriceResponse(BaseModel):
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ticker: str
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prices: list[Price]
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class FinancialMetrics(BaseModel):
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ticker: str
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report_period: str
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period: str
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currency: str
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market_cap: float | None
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enterprise_value: float | None
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price_to_earnings_ratio: float | None
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price_to_book_ratio: float | None
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price_to_sales_ratio: float | None
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enterprise_value_to_ebitda_ratio: float | None
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enterprise_value_to_revenue_ratio: float | None
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free_cash_flow_yield: float | None
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peg_ratio: float | None
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gross_margin: float | None
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operating_margin: float | None
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net_margin: float | None
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return_on_equity: float | None
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return_on_assets: float | None
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return_on_invested_capital: float | None
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asset_turnover: float | None
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inventory_turnover: float | None
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receivables_turnover: float | None
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days_sales_outstanding: float | None
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operating_cycle: float | None
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working_capital_turnover: float | None
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current_ratio: float | None
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quick_ratio: float | None
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cash_ratio: float | None
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operating_cash_flow_ratio: float | None
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debt_to_equity: float | None
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debt_to_assets: float | None
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interest_coverage: float | None
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revenue_growth: float | None
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earnings_growth: float | None
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book_value_growth: float | None
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earnings_per_share_growth: float | None
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free_cash_flow_growth: float | None
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operating_income_growth: float | None
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ebitda_growth: float | None
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payout_ratio: float | None
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earnings_per_share: float | None
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book_value_per_share: float | None
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free_cash_flow_per_share: float | None
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class FinancialMetricsResponse(BaseModel):
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financial_metrics: list[FinancialMetrics]
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class LineItem(BaseModel):
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ticker: str
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report_period: str
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period: str
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currency: str
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# Allow additional fields dynamically
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model_config = {"extra": "allow"}
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class LineItemResponse(BaseModel):
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search_results: list[LineItem]
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class InsiderTrade(BaseModel):
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ticker: str
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issuer: str | None
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name: str | None
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title: str | None
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is_board_director: bool | None
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transaction_date: str | None
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transaction_shares: float | None
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transaction_price_per_share: float | None
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transaction_value: float | None
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shares_owned_before_transaction: float | None
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shares_owned_after_transaction: float | None
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security_title: str | None
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filing_date: str
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class InsiderTradeResponse(BaseModel):
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insider_trades: list[InsiderTrade]
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class CompanyNews(BaseModel):
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category: str | None = None
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ticker: str
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title: str
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related: str | None = None
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source: str
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date: str | None = None
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url: str
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summary: str | None = None
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class CompanyNewsResponse(BaseModel):
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news: list[CompanyNews]
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class CompanyFacts(BaseModel):
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ticker: str
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name: str
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cik: str | None = None
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industry: str | None = None
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sector: str | None = None
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category: str | None = None
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exchange: str | None = None
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is_active: bool | None = None
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listing_date: str | None = None
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location: str | None = None
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market_cap: float | None = None
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number_of_employees: int | None = None
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sec_filings_url: str | None = None
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sic_code: str | None = None
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sic_industry: str | None = None
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sic_sector: str | None = None
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website_url: str | None = None
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weighted_average_shares: int | None = None
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class CompanyFactsResponse(BaseModel):
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company_facts: CompanyFacts
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class Position(BaseModel):
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"""Position information - for Portfolio mode"""
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long: int = 0 # Long position quantity (shares)
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short: int = 0 # Short position quantity (shares)
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long_cost_basis: float = 0.0 # Long position average cost
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short_cost_basis: float = 0.0 # Short position average cost
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class Portfolio(BaseModel):
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"""Portfolio - for Portfolio mode"""
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cash: float = 100000.0 # Available cash
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positions: dict[str, Position] = {} # ticker -> Position mapping
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# Margin requirement (0.0 means shorting disabled, 0.5 means 50% margin)
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margin_requirement: float = 0.0
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margin_used: float = 0.0 # Margin used
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class AnalystSignal(BaseModel):
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signal: str | None = None
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confidence: float | None = None
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reasoning: dict | str | None = None
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# Extended fields for richer signal information
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reasons: list[str] | None = None # Core drivers/reasons for the signal
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risks: list[str] | None = None # Key risk factors
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invalidation: str | None = None # Conditions that would invalidate the thesis
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next_action: str | None = None # Suggested next action for PM
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# Valuation-related fields
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intrinsic_value: float | None = None # DCF intrinsic value
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fair_value_range: dict | None = None # {bear, base, bull} fair value range
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value_gap_pct: float | None = None # Value gap percentage
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valuation_methods: list[str] | None = None # List of valuation methods used
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max_position_size: float | None = None # For risk management signals
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class TickerAnalysis(BaseModel):
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ticker: str
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analyst_signals: dict[str, AnalystSignal] # agent_name -> signal mapping
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class AgentStateData(BaseModel):
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tickers: list[str]
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portfolio: Portfolio
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start_date: str
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end_date: str
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ticker_analyses: dict[str, TickerAnalysis] # ticker -> analysis mapping
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class AgentStateMetadata(BaseModel):
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show_reasoning: bool = False
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model_config = {"extra": "allow"}
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__all__ = [
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"Price",
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"PriceResponse",
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"FinancialMetrics",
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"FinancialMetricsResponse",
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"LineItem",
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"LineItemResponse",
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"InsiderTrade",
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"InsiderTradeResponse",
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"CompanyNews",
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"CompanyNewsResponse",
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"CompanyFacts",
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"CompanyFactsResponse",
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"Position",
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"Portfolio",
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"AnalystSignal",
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"TickerAnalysis",
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"AgentStateData",
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"AgentStateMetadata",
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]
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