MemoryPlus

Problem Statement

This project is an intelligent Telegram bot that revolutionizes how users interact with blockchain data and personal information management. The bot combines three core functionalities:🧠AI-Powered Memory System: Users can naturally store personal experiences, preferences, and information through conversational AI. The system uses dynamic schema inference to automatically categorize and structure data, allowing users to recall information with natural language queries like "What restaurants did I like in Tokyo?"⛓️Multi-Chain Token Integration: Real-time token data integration across three major blockchains (Ethereum Mainnet, Flow EVM, and Rootstock) using Blockscout APIs. Users can search tokens, view prices, holder counts, trading volumes, and market charts through simple commands.💬Smart Conversation Interface: Powered by GPT-4, the bot understands context and intent, automatically determining whether users want to store memories, recall information, fetch blockchain data, or simply chat. The AI maintains conversation history and provides contextual responses.Key features include persistent memory storage, natural language processing, multi-chain blockchain data aggregation, and seamless user experience through Telegram's familiar interface.

Solution

This project leverages a modern tech stack optimized for rapid development and scalability:Backend Architecture (Node.js/TypeScript):Telegraf.jsfor Telegram Bot API integrationOpenAI GPT-4for natural language processing and intent classificationSQLitedatabase for rapid prototyping with structured memory storageExpress.jsserver for health checks and potential API expansionAI & Memory System:Custom prompt engineering to classify user intents (store/recall/blockchain/chat)Dynamic schema inference that creates data structures on-the-flyContextual memory recall using text search and categorizationChat history maintenance for conversational contextBlockchain Integration:Blockscout APIsacross three chains: Ethereum Mainnet, Flow EVM, and RootstockRESTful API integration for token search, details, and market chartsError handling and fallback mechanisms for multiple chain queriesCustom response formatting for optimal mobile displayDeployment:Railwayfor backend hosting with automatic deploymentsEnvironment-based configuration for secure API key managementTypeScript compilation with proper type safetyNotable Technical Achievements:Single conversational interface that intelligently routes to different functionalitiesReal-time multi-chain data aggregation without requiring users to specify chainsMemory system that adapts to user's personal data patternsResponsive error handling across all external API dependenciesThe hackiest part was implementing dynamic schema inference - the AI analyzes user input patterns and automatically creates appropriate data categories and metadata structures, making the memory system truly adaptive to each user's needs without predefined schemas.