Technical Architecture

VECTOR IQ+ Bot is built on a robust, scalable architecture designed for reliability, performance, and accurate analysis.

Backend Infrastructure

Python-Based Core

  • Asynchronous Processing: Non-blocking operations for optimal performance

  • Concurrent API Calls: Parallel data fetching from multiple sources

  • Proper Error Handling: Graceful degradation when services are unavailable

  • Type Safety: Comprehensive type hints and validation

  • Modular Design: Clean separation of concerns across components

Modular Feature System

  • Independent Analysis Modules: Each analysis type as a separate feature class

  • Pluggable Architecture: Easy addition of new analysis features

  • Weighted Scoring System: Configurable importance weights per feature

  • Grade Calculation Engine: Sophisticated scoring algorithms

  • Feature Composition: Flexible combination of analysis results

Data Processing Pipeline

  1. Input Validation: Contract address and chain validation

  2. Parallel Data Fetching: Simultaneous API calls to all data sources

  3. Data Normalization: Consistent data format across sources

  4. Analysis Execution: Independent feature analysis with error handling

  5. Grade Calculation: Weighted scoring and letter grade assignment

  6. Result Compilation: Professional formatting and card generation

Performance Optimizations

Smart Caching System

  • Selective Caching Strategy: Only cache slow-changing data

  • Cache Categories:

    • Cached Data: Contract source code, audit results, creator analysis

    • Always Fresh: Market data, holder counts, prices, trading volume

  • TTL Management: 10-minute cache expiration for optimal freshness

  • Memory Efficiency: Automatic cleanup of expired cache entries

Efficient Data Fetching

  • Parallel API Calls: Simultaneous requests to multiple endpoints

  • Timeout Management: Configurable timeouts with retry logic

  • Rate Limit Handling: Proper backoff and retry mechanisms

  • Fallback Systems: Multiple data sources for each analysis type

  • Connection Pooling: Reused HTTP connections for better performance

Response Time Optimization

  • Target Performance: 10-15 seconds for complete analysis

  • Bottleneck Identification: Monitoring of slow API endpoints

  • Progressive Response: Status updates during long operations

  • Chart Feature Removal: Disabled chart generation for speed improvement

Data Architecture

Multi-Source Integration

Primary APIs (6+ sources):

  • EVA AI: Contract auditing and security analysis

  • GoPlus: Multi-chain security and holder data

  • Token Sniffer: Security analysis and malicious databases

  • DexScreener: Real-time market data and enhanced information

  • Etherscan Family: Contract verification and transaction data

  • OpenAI: AI-powered contract analysis and assistance

Data Flow Architecture

User Input → Validation → Parallel API Calls → Data Normalization → 
Feature Analysis → Grade Calculation → Card Generation → Response

Error Resilience

  • Graceful Degradation: Analysis continues with available data sources

  • Fallback Hierarchies: Primary, secondary, and tertiary data sources

  • Partial Analysis: Meaningful results even with limited data

  • Error Categorization: Different handling for temporary vs permanent failures

Analysis Engine

Feature Weight System

Security Analysis: 2.0x weight (most critical)
Holder Analysis: 1.5x weight (whale concentration risk)
Wash Trading Analysis: 1.3x weight (manipulation detection)
Market Analysis: 1.0x weight (liquidity and trading)
Sniper Analysis: 1.0x weight (launch patterns)
Link Analysis: 0.5x weight (informational)

Scoring Algorithm

  • Base Score Calculation: Individual feature scoring (0-100)

  • Risk Factor Application: Negative adjustments for identified risks

  • Positive Factor Bonuses: Rewards for good indicators

  • Weighted Combination: Feature scores combined using weight system

  • Grade Assignment: Numerical score converted to A+ through F grades

Pattern Detection Algorithms

  • Wash Trading Detection: Custom algorithms for trading pattern analysis

  • Holder Concentration Analysis: Whale detection and risk assessment

  • Contract Risk Assessment: Security vulnerability identification

  • Market Manipulation Detection: Volume and price pattern analysis

Visual Generation System

Scoring Card Engine

  • Template System: Multiple card templates based on scores

  • Dynamic Image Generation: Real-time card creation with current data

  • Professional Typography: Cross-platform font system with fallbacks

  • Color Psychology: Risk-appropriate color coding throughout

  • Brand Consistency: Vector AI branding and styling standards

Image Processing Pipeline

  1. Data Extraction: Token info, grades, market data compilation

  2. Template Selection: Appropriate template based on overall score

  3. Dynamic Composition: Text and visual element positioning

  4. Logo Integration: Automatic token logo fetching and processing

  5. Quality Assurance: Final image optimization and validation

Reliability & Monitoring

Error Handling Strategy

  • Comprehensive Logging: Detailed logs for debugging and monitoring

  • Exception Management: Proper error catching and recovery

  • User-Friendly Messages: Clear error communication to users

  • Monitoring Integration: Health checks and performance monitoring

Data Quality Assurance

  • Cross-Source Validation: Verification between multiple data sources

  • Anomaly Detection: Identification of unusual or suspicious data

  • Confidence Scoring: Data quality indicators in analysis results

  • Manual Review Triggers: Flags for unusual patterns requiring review

Scalability Design

  • Stateless Architecture: No server-side session dependencies

  • Horizontal Scaling: Ability to run multiple bot instances

  • Resource Management: Efficient memory and CPU utilization

  • Database Independence: Minimal persistent storage requirements

Security & Privacy

API Security

  • Secure Credential Management: Proper API key storage and rotation

  • Rate Limit Compliance: Respect for all API provider limits

  • HTTPS Enforcement: Encrypted communications with all services

  • Input Sanitization: Comprehensive validation of user inputs

User Privacy

  • Minimal Data Retention: No unnecessary user data storage

  • Anonymous Analysis: No tracking of individual user behavior

  • Secure Communications: Encrypted Telegram API communications

  • Data Minimization: Only collect data necessary for analysis

The technical architecture prioritizes accuracy, performance, and reliability to deliver professional-grade token analysis at scale.

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