📄 中文摘要
构建一个能够自主处理 PDF 文档的 AI 代理，能够理解内容并回答问题，而无需用户干预支付。当前的 RAG 管道通常需要多个组件，包括 PDF 解析、嵌入生成、重排序和 LLM 推理，每个组件都需要独立的计费账户和 API 密钥。通过简化这些流程，可以创建一个只需 70 行 Python 代码的自主代理，显著降低用户的管理负担。
构建一个完全自主的 RAG 代理，能够自付计算费用 (x402 + GPU-Bridge)
📄 English Summary
Build a Fully Autonomous RAG Agent That Pays for Its Own Compute (x402 + GPU-Bridge)
An AI agent capable of autonomously processing PDF documents, understanding their content, and answering questions without user intervention for payment is proposed. Current RAG pipelines typically require multiple components, including PDF parsing, embeddings, reranking, and LLM inference, each necessitating separate billing accounts and API keys. By streamlining these processes, a fully autonomous agent can be created with just 70 lines of Python code, significantly reducing the management burden on users.