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Challenge

Build a Resilient Payment Gateway Dynamic Router with LangChain and LangGraph

Acquisition strain and merchant gateway failures disrupt high-volume payment processing across partner rails. Build a LangGraph stateful agentic workflow to dynamically re-route failed payment transactions based on real-time gateway health, fee structures, and latency profiles. Achieve payment recovery rates above 98% with automated fallback circuit breaking.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Develop a stateful multi-step payment routing workflow using LangGraph and LangChain to dynamically handle processor outages and optimize payment authorization success rates.

Delivery guide

How work is evaluated

Evaluation

Evaluates the dynamic payment router state graph on recovery rate of transactions during simulated processor outages.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

gateway_health_check

Ensures targeted fallback gateway is marked as HEALTHY

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

recovery_rate

Percentage of failed payments successfully re-routed to healthy gateways • target: 0.98 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Construct a stateful graph-based workflow using LangGraph for payment retry and dynamic routing

  • Build dynamic circuit breaker nodes to track real-time payment gateway health metrics

  • Optimize transaction routing based on processing fee, currency, and historical acceptance rates

  • Implement full auditability and fallback execution loops for failed payment authorizations

Resources and assets

Reference links and supporting material

Dataset notes

Dataset of 500 payment transaction event logs including simulated gateway timeout and error responses across multiple global processors.

How this agent runs

Evaluates the dynamic payment router state graph on recovery rate of transactions during simulated processor outages.

Challenge input

JSON containing initial_failed_gateway, error_code, amount, currency, active_gateways_status

LangGraph

Provides graph-based state persistency necessary for robust multi-step retry workflows.

LangChain

Provides prompt templates and LLM integration utilities.

Evaluated output

JSON with target_gateway, retry_permitted, circuit_breaker_tripped, routing_reason

Checks for
  • Ensures targeted fallback gateway is marked as HEALTHY
  • Percentage of failed payments successfully re-routed to healthy gateways • target: 0.98 • range: 0-1
Proof of success
  • Benchmark: Payment Gateway Infrastructure Resiliency Suite
  • Recovery Rate target: 98%
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • LangGraph · Required
  • Langchain · Optional
  • LangChain · Optional
Orchestration
  • LangGraph · Required
  • Langchain · Optional
  • LangChain · Optional

Evaluation contract

  • gateway_health_check · Weight 1
  • recovery_rate · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Build a Resilient Payment Gateway Dynamic Router with LangChain and LangGraph