Spaces:
Sleeping
Sleeping
| """ | |
| Report viewer component for displaying analysis results. | |
| """ | |
| from typing import Any, Dict, List, Optional, Union | |
| import gradio as gr | |
| from data.providers.base import DataProvider | |
| from graph.state.trading_state import TechnicalWorkflowState | |
| from graph.workflows.comprehensive_workflow import ComprehensiveState | |
| from utils.cost_tracker import format_cost | |
| def format_config_info(config: Dict[str, Any]) -> str: | |
| """ | |
| Format configuration information for display. | |
| Args: | |
| config: Configuration dictionary | |
| Returns: | |
| Markdown formatted configuration info | |
| """ | |
| if not config: | |
| return "" | |
| lines = [] | |
| lines.append("### ⚙️ Analysis Configuration") | |
| lines.append("") | |
| # Indicator parameters | |
| if "indicator_parameters" in config: | |
| params = config["indicator_parameters"] | |
| lines.append("**Indicator Parameters:**") | |
| lines.append(f"- RSI Period: {params.get('rsi_period', 14)}") | |
| lines.append( | |
| f"- MACD: Fast={params.get('macd_fast', 12)}, Slow={params.get('macd_slow', 26)}, Signal={params.get('macd_signal', 9)}" | |
| ) | |
| lines.append( | |
| f"- Stochastic: K={params.get('stoch_k_period', 14)}, D={params.get('stoch_d_period', 3)}" | |
| ) | |
| lines.append("") | |
| # Data providers | |
| if "data_providers" in config: | |
| providers = config["data_providers"] | |
| lines.append("**Data Sources:**") | |
| lines.append(f"- OHLC: {providers.get('ohlc_primary', 'yfinance')}") | |
| lines.append( | |
| f"- Fundamentals: {providers.get('fundamentals_primary', 'alpha_vantage')}" | |
| ) | |
| lines.append("") | |
| return "\n".join(lines) | |
| def format_cost_summary(cost_summary: Optional[Dict[str, Any]]) -> str: | |
| """ | |
| Format cost tracking summary for display. | |
| Args: | |
| cost_summary: Cost summary dictionary from CostTracker | |
| Returns: | |
| Markdown formatted cost summary | |
| """ | |
| if not cost_summary: | |
| return "" | |
| lines = [] | |
| lines.append("### 💰 Analysis Cost") | |
| lines.append("") | |
| total_cost = cost_summary.get("total_cost", 0.0) | |
| total_tokens = cost_summary.get("total_tokens", 0) | |
| call_count = cost_summary.get("call_count", 0) | |
| lines.append(f"**Total Cost:** {format_cost(total_cost)}") | |
| lines.append(f"**Total Tokens:** {total_tokens:,}") | |
| lines.append(f"**API Calls:** {call_count}") | |
| if call_count > 0: | |
| avg_cost = cost_summary.get("average_cost_per_call", 0.0) | |
| lines.append(f"**Average per Call:** {format_cost(avg_cost)}") | |
| # Show per-agent breakdown if available | |
| agent_costs = cost_summary.get("agent_costs", {}) | |
| if agent_costs: | |
| lines.append("") | |
| lines.append("<details>") | |
| lines.append("<summary><b>Cost by Agent</b> (click to expand)</summary>") | |
| lines.append("") | |
| for agent_name, cost in sorted( | |
| agent_costs.items(), key=lambda x: x[1], reverse=True | |
| ): | |
| lines.append(f"- **{agent_name}:** {format_cost(cost)}") | |
| lines.append("") | |
| lines.append("</details>") | |
| lines.append("") | |
| lines.append("---") | |
| lines.append("") | |
| return "\n".join(lines) | |
| def get_asset_guidance(ticker: str) -> str: | |
| """ | |
| Get asset-specific guidance and warnings based on asset type. | |
| Args: | |
| ticker: Asset ticker symbol | |
| Returns: | |
| Markdown formatted guidance/warning string | |
| """ | |
| asset_type = DataProvider.detect_asset_type(ticker) | |
| asset_characteristics = DataProvider.get_asset_characteristics(asset_type) | |
| guidance_parts = [] | |
| if asset_type == "crypto": | |
| guidance_parts.append("## 🪙 Cryptocurrency Asset") | |
| guidance_parts.append("") | |
| guidance_parts.append("> **⚠️ HIGH VOLATILITY WARNING**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append( | |
| "> - Cryptocurrencies are **extremely volatile** and can experience 10-20%+ swings in minutes" | |
| ) | |
| guidance_parts.append( | |
| "> - Market operates **24/7 (365 days)** - no market close for risk management" | |
| ) | |
| guidance_parts.append( | |
| "> - **Highly sentiment-driven** - news and social media have immediate impact" | |
| ) | |
| guidance_parts.append( | |
| "> - **Regulatory risk** - government actions can cause instant severe moves" | |
| ) | |
| guidance_parts.append( | |
| "> - **Liquidity varies** - wide spreads possible during volatility" | |
| ) | |
| guidance_parts.append("> - Traditional fundamental analysis **does not apply**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append( | |
| "> **Focus on:** Technical patterns, market sentiment, news, trading volume" | |
| ) | |
| guidance_parts.append("") | |
| elif asset_type == "commodity": | |
| guidance_parts.append("## 🌾 Commodity Futures") | |
| guidance_parts.append("") | |
| guidance_parts.append("> **⚠️ FUTURES CONTRACT NOTICE**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append( | |
| "> - Most commodity tickers represent **futures contracts** with expiration dates" | |
| ) | |
| guidance_parts.append( | |
| "> - **Contract rollover** required - positions may need to be closed before expiry" | |
| ) | |
| guidance_parts.append( | |
| "> - **Contango/backwardation** affects long-term holding costs" | |
| ) | |
| guidance_parts.append( | |
| "> - **High leverage** inherent in futures - margin requirements apply" | |
| ) | |
| guidance_parts.append( | |
| "> - **Gap risk** from overnight geopolitical/weather events" | |
| ) | |
| guidance_parts.append("> - Traditional financial metrics **do not apply**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append( | |
| "> **Focus on:** Supply/demand dynamics, inventory levels, weather, geopolitical events" | |
| ) | |
| guidance_parts.append("") | |
| elif asset_type == "index": | |
| guidance_parts.append("## 📈 Market Index") | |
| guidance_parts.append("") | |
| guidance_parts.append("> **ℹ️ INDEX TRACKING NOTICE**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append( | |
| "> - Indices **cannot be traded directly** - use ETFs, futures, or options" | |
| ) | |
| guidance_parts.append( | |
| "> - Represents **weighted basket** of underlying securities" | |
| ) | |
| guidance_parts.append( | |
| "> - **Sector composition** affects behavior - tech-heavy indices more volatile" | |
| ) | |
| guidance_parts.append( | |
| "> - **Diversification** reduces single-stock risk but limits upside" | |
| ) | |
| guidance_parts.append("> - Traditional company fundamentals **do not apply**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append( | |
| "> **Focus on:** Macro trends, sector rotation, interest rates, earnings season" | |
| ) | |
| guidance_parts.append("") | |
| elif asset_type == "forex": | |
| guidance_parts.append("## 💱 Foreign Exchange") | |
| guidance_parts.append("") | |
| guidance_parts.append("> **⚠️ CURRENCY PAIR NOTICE**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append( | |
| "> - Forex markets are **highly leveraged** (50:1 to 500:1 typical)" | |
| ) | |
| guidance_parts.append( | |
| "> - Market operates **24/5** (Sunday evening to Friday evening)" | |
| ) | |
| guidance_parts.append( | |
| "> - **Macro-driven** - central bank policy, interest rates, geopolitical events" | |
| ) | |
| guidance_parts.append( | |
| "> - **Bid-ask spreads** vary by broker and market conditions" | |
| ) | |
| guidance_parts.append("> - Traditional equity fundamentals **do not apply**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append( | |
| "> **Focus on:** Interest rate differentials, economic data, central bank policy" | |
| ) | |
| guidance_parts.append("") | |
| elif asset_type == "stock": | |
| # For stocks, just add a brief note about traditional analysis | |
| guidance_parts.append("## 📊 Equity Stock") | |
| guidance_parts.append("") | |
| guidance_parts.append("> **ℹ️ Traditional equity analysis applies**") | |
| guidance_parts.append("> ") | |
| guidance_parts.append("> This is a publicly traded stock. Analysis includes:") | |
| guidance_parts.append("> - Financial fundamentals (earnings, revenue, margins)") | |
| guidance_parts.append("> - Technical indicators and chart patterns") | |
| guidance_parts.append("> - News and market sentiment") | |
| guidance_parts.append("> - Company-specific events and announcements") | |
| guidance_parts.append("") | |
| return "\n".join(guidance_parts) | |
| def create_timeframe_alignment_indicator( | |
| alignment_score: float, trend_direction: str = "unknown" | |
| ) -> str: | |
| """ | |
| Create a visual indicator for timeframe alignment. | |
| Args: | |
| alignment_score: Alignment score (0-1) | |
| trend_direction: Overall trend direction (bullish, bearish, mixed) | |
| Returns: | |
| Visual indicator string with emoji and description | |
| """ | |
| # Determine alignment strength | |
| if alignment_score >= 0.75: | |
| strength = "Strong" | |
| emoji = "🟢🟢🟢" | |
| elif alignment_score >= 0.5: | |
| strength = "Moderate" | |
| emoji = "🟢🟢" | |
| elif alignment_score >= 0.25: | |
| strength = "Weak" | |
| emoji = "🟡" | |
| else: | |
| strength = "Conflicting" | |
| emoji = "🔴" | |
| # Add trend direction | |
| if trend_direction.lower() == "bullish": | |
| direction_emoji = "📈" | |
| elif trend_direction.lower() == "bearish": | |
| direction_emoji = "📉" | |
| else: | |
| direction_emoji = "↔️" | |
| return f"{emoji} {direction_emoji} {strength} Alignment ({alignment_score:.0%})" | |
| def format_timeframe_context(timeframe_context: Dict[str, Any]) -> str: | |
| """ | |
| Format timeframe context information for display. | |
| Args: | |
| timeframe_context: Timeframe context dict | |
| Returns: | |
| Formatted string | |
| """ | |
| if not timeframe_context: | |
| return "" | |
| label = timeframe_context.get("label", "unknown") | |
| scope = timeframe_context.get("scope", "trading") | |
| hold_duration = timeframe_context.get("hold_duration", "varies") | |
| weight = timeframe_context.get("weight", 0.5) | |
| return f"**Timeframe:** {label} | **Scope:** {scope.title()} | **Expected Hold:** {hold_duration} | **Weight:** {weight:.1f}" | |
| def create_report_viewer() -> gr.Markdown: | |
| """ | |
| Create report viewer component. | |
| Returns: | |
| Gradio Markdown component for displaying reports | |
| """ | |
| return gr.Markdown( | |
| label="Analysis Report", | |
| value="Analysis report will appear here...", | |
| ) | |
| def format_error_report(error_message: str) -> str: | |
| """ | |
| Format error message as report. | |
| Args: | |
| error_message: Error message | |
| Returns: | |
| Markdown formatted error report | |
| """ | |
| return f"""# ⚠️ Analysis Error | |
| An error occurred during analysis: | |
| ``` | |
| {error_message} | |
| ``` | |
| Please check: | |
| - Ticker symbol is valid | |
| - Internet connection is working | |
| - API keys are configured (if using Alpha Vantage) | |
| - Try a different timeframe | |
| """ | |
| def format_progress_message(current_agent: str) -> str: | |
| """ | |
| Format progress message during analysis. | |
| Args: | |
| current_agent: Currently executing agent | |
| Returns: | |
| Progress message | |
| """ | |
| agent_display = current_agent.replace("_", " ").title() | |
| return f"""# 🔄 Analysis in Progress | |
| Currently running: **{agent_display}** | |
| Please wait while the multi-agent system analyzes the market data... | |
| **Workflow Steps:** | |
| 1. ✅ Fetch Market Data | |
| 2. 🔄 Indicator Agent - Calculate technical indicators | |
| 3. ⏳ Pattern Agent - Identify chart patterns | |
| 4. ⏳ Trend Agent - Analyze trends | |
| 5. ⏳ Decision Agent - Generate recommendation | |
| 6. ⏳ Generate Charts | |
| """ | |