feat: Add X402 payment method support to Python human-in-the-loop samples

[jorellis]

This PR introduces support for the x402 payment method within the Python human-in-the-loop agent scenarios. It enables the simulation of x402-compatible transactions across the Merchant, Shopping, and Payment Processor agents.

Key Changes:

• Documentation: Added a detailed README.md for the x402 scenario, including setup and execution instructions.

• Scripting: Updated run.sh to accept a --payment-method argument (defaulting to CARD).

• Merchant Agent:

  • Updated catalog_agent.py to generate CartMandate artifacts with x402 specific PaymentMethodData when enabled.
  • Updated tools.py to route x402 payments to the correct processor.

• Payment Processor Agent:

  • Enhanced tools.py to handle PAYMENT_METHOD environment variable.
  • Implemented logic to process x402 payment mandates, skipping the OTP challenge and credential provider lookup where appropriate (using mock/dummy clients).
  • Added logic to generate x402-specific payment receipts.

• Shopping Agent:

  • Updated tools.py to co nstruct PaymentMandates with the correct method_name and details for x402.
  • Updated payment_method_collector/tools.py to mock x402 payment payloads when the payment method is set to x402.

• Credentials Provider Agent:

  • Added a mock "x402_wallet" to the account_manager.py.
  • Updated tools.py to recognize https://www.x402.org/ as a supported method.

[gemini-code-assist]

Summary of Changes

Hello @jorellis, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the agent-based simulation environment by introducing comprehensive support for the x402 payment method. It allows for end-to-end testing of x402-compatible transactions within the human-in-the-loop agent scenarios, ensuring that all relevant agents correctly process and interact with this new payment type. The changes include updates to core logic for payment processing, credential handling, and user interaction flows, alongside improved documentation for ease of use.

Highlights

• x402 Payment Method Integration: Full support for the x402 payment method has been added across the Merchant, Shopping, and Payment Processor agents, enabling simulation of x402-compatible transactions.
• Configurable Payment Method: The run.sh script now accepts a --payment-method argument, allowing users to easily switch between CARD (default) and x402 payment scenarios.
• Updated Documentation: A comprehensive README.md has been added for the x402 scenario, detailing setup, execution, and interaction steps.
• Mocking for x402: For x402 payments, the system now uses mock clients and skips certain steps like OTP challenges and direct credential provider lookups, streamlining the simulation.
• Agent-Specific Logic: Each agent (Merchant, Shopping, Payment Processor, Credentials Provider) has been updated to correctly handle x402-specific data structures, routing, and processing flows.

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[gemini-code-assist]

Code Review

This pull request successfully introduces support for the x402 payment method across various agents in the human-in-the-loop scenario. The changes are well-contained and primarily involve conditional logic based on the selected payment method, which is appropriate for extending functionality.

My review focuses on improving robustness, consistency, and maintainability. I've identified a few areas for improvement:

• The shell script for argument parsing could be more robust against missing arguments.
• There's a potential logic issue in payment method eligibility checks that could be tightened.
• I've noticed a discrepancy between the documentation and the implementation regarding the OTP challenge flow for x402.
• There are opportunities to improve code consistency by passing parameters instead of reading environment variables in functions.
• Finally, I've suggested replacing magic strings with constants to enhance maintainability.

Overall, these are solid changes that accomplish the goal of the PR. The suggested refinements aim to make the code more robust and easier to maintain.