### Agent A2Z Pay SDK [GitHub](https://github.com/aiagenta2z/agent_a2z_payment) | [Website AI Agent A2Z Pay](https://www.aiagenta2z.com/agent/agent-a2z-pay) | [Reviews](https://www.deepnlp.org/store/pub/pub-aiagenta2z) AgentA2Z Pay SDK can help you integrate various payment methods (Stripe,Paypal,Alipay,WeChat) into your agent workflow and you can define when and where to charge money or create (AI Agent A2Z/DeepNLP API Credit) in the workflow. Payment in AI Agent Workflow Example: 1. Render an AIGC Image thumbnail to user and charge $1 dollars to render the 4K version per each run. 2. Charge 'buy me a coffee' checkout at the end of a Finance/Med/Literature Deep Research before output the final report. 3. Ask for Tips of a few CNY by Scanning QR code to continue fixing bugs in the AI Coding scenario. 4. E-Commerce AI shopping to allow users to confirm the final payment to complete the transaction. **AgentA2ZPayment Checkout Integration**<br> Checkout Card and Playground Result <img src="https://raw.githubusercontent.com/aiagenta2z/agent_a2z_payment/refs/heads/main/docs/credit_card_add.jpg" style="height:800px;" alt="AI Agent Workflow Payment"> **Payment Options** | Platform | URL | |--------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Credit Card | Supported Credit Card using the Stripe Python Integration, including the checkout, webhook | | Stripe | Supported, For Stripe Sandbox/Live PK, SK, Webhook Secret definition, see [Stripe Doc](https://docs.stripe.com/api) | | PayPal | Supported, For Client ID, Secret and Webhook ID, See Doc [Paypal Doc](https://developer.paypal.com/home/) | | AgentA2Z Pay | WIP, Payment using API credit by [AI AGENT A2Z Agent Platform](https://www.aiagenta2z.com) / [DeepNLP OneKey MCP & Agent API](https://www.deepnlp.org/workspace/billing) credit, [OneKey Router Website](https://www.deepnlp.org/agent/onekey-ai-agent-router) and [Doc OneKey Router API Benifits](https://www.deepnlp.org/doc/onekey_mcp_router) | | Alipay | WIP, See [Alipay Developer Doc](https://opendocs.alipay.com) | | WeChat Pay | WIP, See [WeChat Pay Developer Doc](https://pay.weixin.qq.com/static/applyment_guide/applyment_index.shtml) | Supported Environment | Platform | URL | |----------|----------| | Python | Pypi | | NodeJs | NodeJS | ## Brief Introduction of Different Payment Process **Stripe**: Requires two steps: Create Payment Intent return a client_secret, Start Payment in the Client Side and then finish payment, Post Web Hook on **PayPal**: Requires two steps: Create Order (server-side, returns approval_link) and Capture Order (server-side, after user approval/return). **Agent A2Z Payment**: Requires one step of unified credit deduction A2Z Payment on aiagenta2z.com/deepnlp.org right after payment confirmation **Alipay/WeChat Pay**: Requires one step: Unified Order/Create Payment (server-side, returns QR Code URL). Payment is completed via webhook after the user scans the code. ## Tutorial Let's begin with a workflow that charge user per tokens consumed, Example will charge $1. If user pays successfully, the agent loop will continue and return more things, otherwise it will await till timeout and return a checkout fail card. **Install** ```commandline pip install agent-a2z-payment ``` Run complete app example at [Payment Agent App](https://github.com/aiagenta2z/agent_a2z_payment/blob/main/app/payment_agent_app/app.py) ```python import agent_a2z_payment import uuid from agent_a2z_payment.core import get_payment_sdk, PaymentWaitingMode, Environment from agent_a2z_payment.core import _get_paypal_access_token environment = Environment.SANDBOX.value payment_agent = get_payment_sdk(env=environment) ### Define server endpoint, e.g., using FastAPI: @app.post("/api/chat") async def chat(messages: list = Body(...) , kwargs: dict = Body(...)): # 0. Process input and initialize print (f"DEBUG: Input messages: {messages} kwargs: {kwargs}") # 1. LLM/Agent decides the cost of the task (e.g., 0.5 dollars for a report) ### Replace with actual logic to determine the required payment amount and currency. ### e.g. output = payment_agent.calculate_payment(messages) amount = 1.00 # Example amount currency = "USD" print (f"Payment Agent calculated required amount: {amount} {currency}") # 2. Create an order and prepare for asynchronous waiting order = payment_agent.create_order(amount, currency) order_id = order.get("order_id", str(uuid.uuid4())) # 3. Create payment intent and get the checkout card HTML/JS ## payment_method: all,stripe,paypal,agenta2z,alipay,wechat,etc checkout_result = payment_agent.checkout(payment_method="all", order_id=order_id, amount=amount, currency=currency) checkout_html = checkout_result.get("checkout_html", "") checkout_js = checkout_result.get("checkout_js", "") ### code to format the HTML/JS for streaming back to the front-end # message_id = get_new_message_id() ## Yield back the checkout_html and checkout_js ## Omitted # 4. Generator function to wait for payment and stream the final response generator = payment_stream_generator( order_id, message_id, chunk_list, payment_agent.orders ) return StreamingResponse(generator, media_type="text/event-stream") @app.post("/stripe/webhook") async def stripe_webhook(request: Request): ### STRIPE WEBHOOK IMPLEMENTATION ### - Verify the signature (Stripe-Signature header). ### - Handle event types (e.g., 'checkout.session.completed', 'payment_intent.succeeded'). @app.post("/paypal/webhook") async def paypal_webhook(request: Request): ### PAYPAL WEBHOOK IMPLEMENTATION ### - Verify the authenticity of the webhook sender. ### - Handle the relevant payment completion event. ### - Signal the waiting agent workflow as done in the Stripe webhook. ``` Remember to put necessary Environment Keys ``` STRIPE_API_KEY_PK_TEST=pk_test_xxxx STRIPE_API_KEY_SK_TEST=sk_test_xxxx STRIPE_API_KEY_PK_LIVE=pk_xxxx STRIPE_API_KEY_SK_LIVE=sk_xxxx STRIPE_WEBHOOK_SECRET=xxxx PAYPAL_CLIENT_ID_TEST=xxxx PAYPAL_SECRET_TEST=xxxx PAYPAL_CLIENT_ID_LIVE=xxxx PAYPAL_SECRET_LIVE=xxxx PAYPAL_WEBHOOK_ID=xxxx AGENT_A2Z_API_KEY_TEST=a2zt_xxxxxxxx AGENT_A2Z_API_KEY_LIVE=a2zl_xxxxxxxx ``` Run your app workflow, you can see the fully integrated App as in the playground. ```commandline git clone https://github.com/aiagenta2z/agent_a2z_payment cd ./agent_a2z_payment/app/payment_agent_app ## Start Server at 7000 port uvicorn app:app --port 7000 ## Visit http://127.0.0.1:7000/ ## To Expose Your Local Server to Public URL for Web hook Testing ngrok http 7000 # copy and pase the url to each payment site # Example: https://zincky-kenton-cloudily-xxxxx.ngrok-free.dev -> http://localhost:7000 ## Stripe Webhook https://zincky-kenton-cloudily-xxxxx.ngrok-free.dev/stripe/webhook ``` ## Payment Scenario ### 1 Preview-to-Pay Example: prompt: Can you help me generate a 4K xxxx images? Assistant: This is preview of generated image (preview_image). Please proceed to checkout to see the 4k full resolution of Image, for 1 image for xxx cents or xxx credits. Description: This scenario is about gating high-value content. The user is allowed to preview a generated asset (the low-resolution image) to confirm its quality and relevance. The system then requires an immediate payment or credit deduction before it completes the final, high-cost rendering of the desired 4K resolution image. This minimizes wasted computational resources on unwanted outputs. Assistant: Sure, The image is generated and preview is here. Please proceed checkout and see full 4K version. **Implementation** ```python ``` ### 2 Post-Workflow Tip (Tipping, Buy me coffee, Red Envelope) prompt: This scenario is about optional, value-based payment for the agent's output, similar to a digital "tip" or "red envelope." The agent completes the resource-intensive task (like generating the PPTs or Reports) and delivers the final, high-value content to the user. Instead of being charged a fixed fee upfront, the user is presented with an option to voluntarily pay a token/credit amount based on how much they like or value the quality of the generated work. This model rewards the developer for creating high-quality, desirable outputs. **Implementation** ```python ``` ### 3 Cost-Based Consumption Description: agent calculate the total tokens/image/commercial APIs/unique data sources consumed, and calculate a price in dollars/credits, etc. **Implementation** ```python ``` ### 4 E-Commerce Checkout This scenario focuses on agent assistance in user transactions. The agent's task is to guide the user through an external e-commerce website and automatically identify and highlight the final payment entry or checkout confirmation element. The agent simplifies the transaction completion process by pointing the user to the precise Call to Action required to finalize the purchase. **Implementation** ```python ``` ### Related [AI Agent Marketplace Registry](https://github.com/aiagenta2z/ai-agent-marketplace) [Open AI Agent Marketplace](https://www.deepnlp.org/store/ai-agent) [MCP Marketplace](https://www.deepnlp.org/store/ai-agent/mcp-server) [OneKey Router AI Agent & MCP Ranking](https://www.deepnlp.org/agent/rankings) [OneKey Agent MCP Router](https://www.deepnlp.org/agent/onekey-mcp-router) [OneKey AGent MCP Router Doc](https://deepnlp.org/doc/onekey_mcp_router) [AI Agent Dataset](https://www.deepnlp.org/store/dataset) [Gemini Nano Banana Agent](https://agent.deepnlp.org/agent/mcp_tool_use?server=aiagenta2z%2Fgemini_mcp_onekey)