From Prompt to Paycheck: Wiring an LLM Chain Into Real Gig Platforms

说明与用途

逐步工作流程，展示如何将LLM链部署为自由职业平台服务，包括输入验证、工具集成、输出格式化和x402支付签名。

问题

Deploying an LLM‑powered service on a gig marketplace requires robust input handling, tool integration, output formatting, and payment collection while keeping the system production‑ready.

结果

The example demonstrates a complete, testable pipeline that can be deployed to a gig marketplace, enabling automated AI services to earn revenue via micropayments.

工作流

• Receive POST webhook from gig platform
• Validate and sanitize the task payload
• Send task to LLM (e.g., gpt‑4o‑mini)
• Optionally invoke external tool (e.g., weather API) based on LLM output
• Format tool result into JSON or markdown
• Create x402 payment request and sign invoice
• Return signed invoice as HTTP response

证据

Below is a self‑contained Flask app that implements the chain, accepts a POST from a gig platform webhook, runs the LLM, and returns an x402‑signed invoice.

来源

Input validation, tool use, post‑processing, retry & fallback are essential for real‑world gigs.

来源