Autonomous Shopping Assistant

๐Ÿ›’ Use Case: Autonomous Shopping Assistant

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Overview

Imagine an AI agent that can autonomously complete entire shopping transactions - from understanding user requirements to finalizing payments - without any human intervention. With tPay SDK, this vision becomes reality. Our shopping assistant demonstrates how AI agents can seamlessly handle complex, multi-step financial workflows while maintaining full autonomy and security.


๐ŸŽฏ The Challenge

Traditional e-commerce requires multiple human interactions:

  • Manual product searching and comparison
  • Balance checking and payment authorization
  • Transaction confirmation and tracking
  • Error handling and retry logic
  • Payment dispute resolution: Manual customer service intervention, lengthy back-and-forth communication, time-consuming escalation processes
  • The biggest pain point: When payments fail or disputes arise, it often takes hours or days of manual communication between customers, merchants, and payment processors to resolve issues.
  • What if an AI agent could handle all of this autonomously through intelligent agent-to-agent communication?


๐Ÿ’ก The Solution: Autonomous Shopping Agent


Our shopping assistant showcases a fully autonomous agent that:

  • ๐Ÿ” Understands Context - Interprets user requirements intelligently
  • ๐Ÿ’ฐ Manages Finances - Checks balances and makes informed decisions
  • ๐Ÿ›๏ธ Shops Intelligently - Searches, compares, and selects optimal products
  • ๐Ÿ’ณ Completes Payments - Handles transactions end-to-end
  • ๐Ÿ”„ Handles Challenges - Automatically retries and resolves payment issues through intelligent agent-to-agent communication

๐Ÿš€ Agent Workflow

graph TD
    A[๐Ÿ‘ค User Request] --> B[๐Ÿ” Get User Agent ID]
    B --> C[๐Ÿ’ฐ Check Agent Balance]
    C --> D[๐Ÿ›๏ธ Search Products]
    D --> E[๐Ÿง  Analyze Options]
    E --> F[๐Ÿ’ฐ Select Best Product]
    F --> G[๐Ÿ’ณ Create Payment]
    G --> H{Payment Status?}
    H -->|โœ… Confirmed| I[๐ŸŽ‰ Purchase Complete]
    H -->|โŒ Rejected| J[๐Ÿ”„ Handle Challenge]
    J --> K[๐Ÿค Agent-to-Agent Communication]
    K --> L[๐Ÿ“‹ Gather Additional Context]
    L --> M[๐Ÿ” Retry Payment with Enhanced Data]
    M --> H

๐Ÿ’ป Core Implementation

Agent Tool Registration

from tpay import *

# ๐Ÿ› ๏ธ Register custom business logic tools
@tradar_verifier
def search_product(query: str) -> Dict[str, Any]:
    """Intelligent product search with real-time pricing"""
    # You can implement different search tools for agents here like Amazon, Google...etc.
    # And the search function should return formatted response, we provided one sample here
    return {
        "results": [
            {
                "name": "Blue Yeti Microphone", 
                "price": 10, 
                "currency": "XRP", 
                "settlement_network": "xrpl",
                "receiving_agent_id": "merchant_agent_123",
                "id": "mic001"
            }
        ]
    }

@tradar_verifier  
def get_user_agent_id(user_id: str) -> Dict[str, Any]:
    """Retrieve agent ID associated with user"""
    return {"agent_id": "user_agent_456"}

# ๐Ÿ’ณ Initialize tPay financial tools
balance_tool = tpay_toolkit_balance()
payment_tool = tpay_toolkit_payment()

Autonomous Decision Engine

@taudit_verifier
def autonomous_shopping_agent(user_request: str) -> Dict[str, Any]:
    """
    Fully autonomous shopping agent that:
    1. Understands user needs
    2. Checks financial capacity  
    3. Finds optimal products
    4. Completes transactions
    5. Handles payment challenges
    """
    
    # ๐Ÿง  Agent reasoning system
    conversation = [
        {
            "role": "system",
            "content": """You are an autonomous shopping agent with access to:
            
            ๐Ÿ” search_product(query) - Find products matching requirements
            ๐Ÿ’ฐ get_agent_balance(agent_id) - Check available funds  
            ๐Ÿ’ณ create_payment(...) - Execute transactions
            ๐Ÿ†” get_user_agent_id(user_id) - Get user's financial identity
            
            AUTONOMOUS BEHAVIOR:
            - Make ALL decisions independently
            - Choose optimal products within budget
            - Complete purchases without confirmation
            - Handle payment challenges automatically
            - Optimize for user satisfaction and cost efficiency
            """
        },
        {
            "role": "user", 
            "content": user_request
        }
    ]
    
    return run_autonomous_conversation(conversation)

๐ŸŽฌ Live Agent Interaction

User Request

"My user_id is 123, I want to buy a microphone for Alice, please help me decide the most suitable choice within my current balance and complete the purchase for me."

Agent Autonomous Response Flow

๐Ÿ” Step 1: Identity Resolution

๐Ÿค– Agent: "I'll help you find and purchase the perfect microphone for Alice. 
Let me start by getting your agent ID and checking your available balance."

๐Ÿ”ง Tool Call: get_user_agent_id(user_id="123")
โœ… Result: {"agent_id": "agt_456789"}

๐Ÿ’ฐ Step 2: Financial Assessment

๐Ÿ”ง Tool Call: get_agent_balance(agent_id="agt_456789")
โœ… Result: {"balance": 50.0, "currency": "XRP", "network": "xrpl"}

๐Ÿค– Agent: "Great! You have 50 XRP available. Now let me search for 
suitable microphones within your budget."

๐Ÿ›๏ธ Step 3: Intelligent Product Discovery

๐Ÿ”ง Tool Call: search_product(query="microphone Alice recording")
โœ… Result: {
    "results": [
        {
            "name": "Blue Yeti Microphone",
            "price": 10,
            "currency": "XRP", 
            "id": "mic001"
        }
    ]
}

๐Ÿค– Agent: "Perfect! I found the Blue Yeti Microphone for 10 XRP - 
it's well within your budget and excellent for Alice's needs."

๐Ÿ’ณ Step 4: Autonomous Payment Execution

๐Ÿ”ง Tool Call: create_payment(
    agent_id="agt_456789",
    receiving_agent_id="merchant_agent_123", 
    amount=10,
    currency="XRP",
    settlement_network="xrpl"
)

โœ… Result: {
    "status": "confirmed",
    "payment_id": "pay_xyz789",
    "transaction_hash": "0xabc123...",
    "confirmation_time": "2024-01-15T10:30:00Z"
}

๐Ÿค– Agent: "๐ŸŽ‰ Purchase completed successfully! I've bought the Blue Yeti 
Microphone for Alice using 10 XRP. Transaction confirmed on XRPL network. 
Your remaining balance is 40 XRP."

๐Ÿ” Security & Compliance Features

Automatic Audit Trail

Every agent action is automatically tracked and audited:

@taudit_verifier  # ๐Ÿ“Š Automatic compliance tracking
def autonomous_purchase_flow():
    # All agent decisions and tool calls are:
    # โœ… Cryptographically signed
    # โœ… Immutably recorded  
    # โœ… Compliance-verified
    # โœ… Risk-assessed in real-time

Smart Challenge Handling

When payments face verification challenges, our agents communicate directly with each other to resolve disputes autonomously:

# ๐Ÿ›ก๏ธ Intelligent challenge resolution through agent-to-agent communication
if payment_response.status == "failed" and payment_response.challenge is not None:
    # ๐Ÿค Direct agent-to-agent communication (no human intervention)
    challenge_context = agent.communicate_with_merchant_agent(
        challenge_details=payment_response.challenge,
        user_context=user_profile,
        transaction_history=past_transactions
    )
    
    # ๐Ÿ“‹ Agents negotiate and gather required information autonomously
    enhanced_payment_data = agent.gather_additional_context(challenge_context)
    
    # ๐Ÿ” Retry payment with mutually agreed parameters
    resolved_payment = agent.retry_payment_with_enhanced_data(enhanced_payment_data)
    
    # โšก Resolution in seconds, not hours/days

Traditional Process: Human customer service โ†’ Email exchanges โ†’ Manual verification โ†’ 24-48 hours resolution


tPay Agent Process: Agent detects issue โ†’ Agent-to-agent communication โ†’ Autonomous resolution โ†’ 2-5 mins resolution



๐Ÿ“Š Business Impact

For Developers ๐Ÿ‘ฉโ€๐Ÿ’ป

  • 10x Faster Integration: Pre-built financial tools
  • Zero Payment Logic: Built-in transaction handling
  • Automatic Compliance: KYA and audit trails included
  • Multi-Network Support: Solana, XRPL, and more

For Businesses ๐Ÿข

  • Autonomous Operations: 24/7 intelligent purchasing with agentic customer support
  • Higher Conversion Rate: With Smart Challenge in place, agents will be able to resolve conflicts and payment rejections autonomously and efficiently
  • Dramatic Cost Reduction: Eliminate customer service costs for payment disputes (avg. $15-50 per case โ†’ $0.001 per automated resolution)
  • Lightning-Fast Resolution: Agent-to-agent communication resolves disputes in seconds vs. traditional 24-48 hour human processes
  • Risk Mitigation: Built-in fraud protection with real-time agent verification
  • Scalable Architecture: Handle thousands of concurrent transactions and disputes simultaneously

For Users ๐ŸŽฏ

  • Seamless Experience: extremely simplified experience (natural language/ambient agents)
  • Intelligent Decisions: AI optimizes for preferences and budget
  • Secure Transactions: Enterprise-grade security, more reliable than human
  • Multi-Asset Support: Pay with various cryptocurrencies

๐ŸŒŸ Key Differentiators

Traditional E-commercetPay Autonomous Agents
โŒ Manual cart managementโœ… AI-driven product selection
โŒ Manual payment authorizationโœ… Autonomous transaction execution
โŒ Human error-proneโœ… Consistent optimal decisions
โŒ Manual dispute resolution (24-48 hours)โœ… Agent-to-agent autonomous resolution (2-5 seconds)
โŒ Customer service escalation neededโœ… Intelligent agent negotiation
โŒ Limited to business hoursโœ… 24/7 autonomous operation
โŒ Single payment methodโœ… Multi-network crypto payments

๐Ÿš€ Getting Started

Ready to build your own autonomous shopping agent?

# 1๏ธโƒฃ Initialize tPay SDK
import tpay
tpay.tpay_initialize(
    api_key="your_api_key",
    api_secret="your_api_secret", 
    project_id="your_project_id"
)

# 2๏ธโƒฃ Register your business logic
@tpay.tradar_verifier
def your_custom_tool():
    # Your business logic here
    pass

# 3๏ธโƒฃ Create autonomous agent
agent = create_autonomous_agent(
    tools=[your_custom_tool, tpay.payment_tool, tpay.balance_tool],
    autonomy_level="full"
)

# 4๏ธโƒฃ Deploy and watch it work! ๐ŸŽ‰

๐Ÿ“ˆ MORE Real-World Applications...

๐Ÿ›’ E-commerce Platforms

  • Autonomous personal shoppers
  • Smart inventory management
  • Dynamic pricing optimization

๐Ÿฆ Financial Services

  • Automated bill payments (utility bill, subscription, etc.)
  • Investment portfolio management
  • Smart contract executions

๐ŸŽฎ Gaming & Metaverse

  • In-game asset trading
  • NFT marketplace automation
  • Virtual economy management

๐Ÿค– IoT & Smart Devices

  • Autonomous supply (parts, material, etc. ) ordering
  • Smart home expense management
  • Industrial procurement automation

๐Ÿค Agent-to-Agent Commerce

  • Cross-platform payment dispute resolution
  • Automated merchant-customer agent negotiations
  • Real-time transaction verification networks (tRadar as a service)
  • Autonomous refund and chargeback handling

Experience the future of autonomous financial agents with tPay SDK. Where AI intelligence meets seamless transactions. ๐Ÿš€โœจ