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Graph Crypto Analysis

This example implements a complete cryptocurrency research and analysis pipeline that demonstrates end-to-end LLM-driven decision making, from data collection through technical analysis to investment recommendations.

🎯 Core Functionality​

Intelligent Market Analysis System:

  • LLM-driven token selection - The system analyzes market data and intelligently selects tokens for deeper analysis based on real-time market conditions
  • Multi-timeframe analysis - Simultaneously processes data from multiple timeframes (1m, 5m, 15m, 1h, 4h, daily) for comprehensive market view
  • Dynamic decision flow - Every step in the analysis process is guided by LLM decisions, creating adaptive and context-aware analysis

Advanced Technical Analysis:

  • Real-time indicator calculation - Computes technical indicators (RSI, MACD, EMA, Bollinger Bands) using live market data
  • Market sentiment analysis - Analyzes price patterns, volume, and market momentum
  • Risk assessment - Evaluates market volatility and risk metrics for each analyzed token

LLM-Powered Synthesis:

  • Intelligent summarization - Synthesizes complex market data into clear, actionable insights
  • Investment recommendations - Provides data-driven buy/sell/hold recommendations with reasoning
  • Market outlook generation - Creates short-term and macro-level market predictions

🚀 Key Features Demonstrated​

  • Complete Graph Workflow - End-to-end implementation from data ingestion to final recommendations
  • Real API Integration - Uses actual Binance and cryptocurrency APIs for live data
  • LLM Decision Making - Every major decision in the workflow is LLM-driven
  • Advanced State Management - Maintains complex analysis state throughout the process
  • Error Recovery - Robust error handling and fallback mechanisms

📋 Prerequisites​

# Required environment variables
export OPENAI_API_KEY="your-openai-api-key"          # Primary LLM
export ANTHROPIC_API_KEY="your-anthropic-api-key"   # Alternative LLM
export TAVILY_API_KEY="your-tavily-api-key"       # Search engine

🏃 Quick Start​

# Navigate to examples directory
cd spoon-cookbook/example

# Install dependencies
pip install -r requirements.txt

# Run the crypto analysis
python graph_crypto_analysis.py

🔍 What to Observe​

Data Flow Analysis:

  • Watch how the system fetches and processes real market data from multiple sources
  • Observe how the LLM analyzes raw data and makes intelligent decisions
  • See the step-by-step analysis process from data collection to final recommendations

Technical Analysis:

  • Monitor how technical indicators are calculated in real-time
  • Observe how the system correlates different data sources
  • Track how market sentiment is analyzed and quantified

LLM Decision Process:

  • See how the LLM evaluates different tokens and selects analysis targets
  • Watch the synthesis process that combines technical and fundamental analysis
  • Observe how investment recommendations are generated with detailed reasoning

📊 Analysis Output Example​

🔍 MARKET ANALYSIS REPORT
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

📈 SELECTED TOKENS FOR ANALYSIS: BTC, ETH, SOL, ADA

📊 TECHNICAL ANALYSIS:
• BTC/USDT: Bullish momentum, RSI: 68, MACD positive crossover
• ETH/USDT: Consolidation phase, approaching key resistance
• SOL/USDT: Strong uptrend, breaking previous highs
• ADA/USDT: Recovery phase, positive volume momentum

🎯 INVESTMENT RECOMMENDATIONS:
• SHORT-TERM: Consider BTC and SOL for momentum plays
• MEDIUM-TERM: Hold ETH through current consolidation
• RISK ASSESSMENT: Moderate volatility expected in next 24-48 hours

💡 MARKET OUTLOOK:
The current market shows strong bullish momentum with BTC leading...

📁 Source Code & Documentation​

  • GitHub Link: Graph Crypto Analysis
  • Related Files:
    • spoon-core/examples/graph_crypto_analysis.py - Full implementation
    • spoon-core/spoon_ai/tools/crypto_tools.py - Crypto analysis tools
    • spoon-core/spoon_ai/graph/ - Graph system utilities
    • docs/core-concepts/tools.md - Tool system documentation

🎓 Learning Objectives​

This example teaches you:

  • How to build complete end-to-end analysis systems with LLM integration
  • Advanced cryptocurrency market analysis techniques
  • Real-time data processing and technical indicator calculation
  • LLM-driven decision making in complex workflows
  • Error handling and data validation in financial applications

💡 Best Practices Demonstrated​

  • Data Validation - Comprehensive validation of market data and API responses
  • Error Resilience - Robust error handling for network and API failures
  • Performance Optimization - Efficient data processing and caching strategies
  • Security - Safe handling of API keys and sensitive financial data
  • Modular Architecture - Clean separation between data collection, analysis, and presentation

🚀 Key Features Demonstrated​

  • Complete Graph Workflow - End-to-end implementation from data ingestion to final recommendations
  • Real API Integration - Uses actual Binance and cryptocurrency APIs for live data
  • LLM Decision Making - Every major decision in the workflow is LLM-driven
  • Advanced State Management - Maintains complex analysis state throughout the process
  • Error Recovery - Robust error handling and fallback mechanisms

📋 Prerequisites​

# Required environment variables
export OPENAI_API_KEY="your-openai-api-key"          # Primary LLM
export ANTHROPIC_API_KEY="your-anthropic-api-key"   # Alternative LLM
export BINANCE_API_KEY="your-binance-api-key"       # Market data
export BINANCE_SECRET_KEY="your-binance-secret"     # Market data

🏃 Quick Start​

# Navigate to examples directory
cd spoon-cookbook/example

# Install dependencies
pip install -r requirements.txt

# Run the crypto analysis
python graph_crypto_analysis.py

🔍 What to Observe​

Data Flow Analysis:

  • Watch how the system fetches and processes real market data from multiple sources
  • Observe how the LLM analyzes raw data and makes intelligent decisions
  • See the step-by-step analysis process from data collection to final recommendations

Technical Analysis:

  • Monitor how technical indicators are calculated in real-time
  • Observe how the system correlates different data sources
  • Track how market sentiment is analyzed and quantified

LLM Decision Process:

  • See how the LLM evaluates different tokens and selects analysis targets
  • Watch the synthesis process that combines technical and fundamental analysis
  • Observe how investment recommendations are generated with detailed reasoning

📊 Analysis Output Example​

🔍 MARKET ANALYSIS REPORT
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

📈 SELECTED TOKENS FOR ANALYSIS: BTC, ETH, SOL, ADA

📊 TECHNICAL ANALYSIS:
• BTC/USDT: Bullish momentum, RSI: 68, MACD positive crossover
• ETH/USDT: Consolidation phase, approaching key resistance
• SOL/USDT: Strong uptrend, breaking previous highs
• ADA/USDT: Recovery phase, positive volume momentum

🎯 INVESTMENT RECOMMENDATIONS:
• SHORT-TERM: Consider BTC and SOL for momentum plays
• MEDIUM-TERM: Hold ETH through current consolidation
• RISK ASSESSMENT: Moderate volatility expected in next 24-48 hours

💡 MARKET OUTLOOK:
The current market shows strong bullish momentum with BTC leading...

📁 Source Code & Documentation​

  • GitHub Link: Graph Crypto Analysis
  • Related Files:
    • spoon-core/examples/graph_crypto_analysis.py - Full implementation
    • spoon-core/spoon_ai/tools/crypto_tools.py - Crypto analysis tools
    • spoon-core/spoon_ai/graph/ - Graph system utilities
    • docs/core-concepts/tools.md - Tool system documentation

🎓 Learning Objectives​

This example teaches you:

  • How to build complete end-to-end analysis systems with LLM integration
  • Advanced cryptocurrency market analysis techniques
  • Real-time data processing and technical indicator calculation
  • LLM-driven decision making in complex workflows
  • Error handling and data validation in financial applications

💡 Best Practices Demonstrated​

  • Data Validation - Comprehensive validation of market data and API responses
  • Error Resilience - Robust error handling for network and API failures
  • Performance Optimization - Efficient data processing and caching strategies
  • Security - Safe handling of API keys and sensitive financial data
  • Modular Architecture - Clean separation between data collection, analysis, and presentation