PaymanAI provides functionality to send and receive payments (fiat and crypto) on behalf of an AI Agent. To get started:
  1. Sign up at app.paymanai.com to create an AI Agent and obtain your API Key.
  2. Set environment variables (PAYMAN_API_SECRET for your API Key, PAYMAN_ENVIRONMENT for sandbox or production).
This notebook gives a quick overview of integrating PaymanAI into LangChain as a tool. For complete reference, see the API documentation.

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Overview

The PaymanAI integration is part of the langchain-community (or your custom) package. It allows you to:
  • Send payments (send_payment) to crypto addresses or bank accounts.
  • Search for payees (search_payees).
  • Add new payees (add_payee).
  • Request money from customers with a hosted checkout link (ask_for_money).
  • Check agent or customer balances (get_balance).
These can be wrapped as LangChain Tools for an LLM-based agent to call them automatically.

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Integration details

ClassPackageSerializableJS supportPackage latest
PaymanAIlangchain_community❌❌[PyPI Version]
If you’re simply calling the PaymanAI SDK, you can do it directly or via the Tool interface in LangChain.

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Setup

  1. Install the langchain-community (or equivalent) package:
pip install --quiet -U langchain-community
  1. Install the PaymanAI SDK:
pip install paymanai
  1. Set environment variables:
export PAYMAN_API_SECRET="YOUR_SECRET_KEY"
export PAYMAN_ENVIRONMENT="sandbox"
Your PAYMAN_API_SECRET should be the secret key from app.paymanai.com. The PAYMAN_ENVIRONMENT can be sandbox or production depending on your usage.

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Instantiation

Here is an example of instantiating a PaymanAI tool. If you have multiple Payman methods, you can create multiple tools. 
from langchain_community.tools.langchain_payman_tool.tool import PaymanAI

# Instantiate the PaymanAI tool (example)
tool = PaymanAI(
    name="send_payment",
    description="Send a payment to a specified payee.",
)

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Invocation

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Invoke directly with args

You can call tool.invoke(...) and pass a dictionary matching the tool’s expected fields. For example: 
response = tool.invoke({
    "amount_decimal": 10.00,
    "payment_destination_id": "abc123",
    "customer_id": "cust_001",
    "memo": "Payment for invoice #XYZ"
})

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Invoke with ToolCall

When used inside an AI workflow, the LLM might produce a ToolCall dict. You can simulate it as follows: 
model_generated_tool_call = {
    "args": {
        "amount_decimal": 10.00,
        "payment_destination_id": "abc123"
    },
    "id": "1",
    "name": tool.name,
    "type": "tool_call",
}
tool.invoke(model_generated_tool_call)

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Using the Tool in a Chain or Agent

You can bind a PaymanAI tool to a LangChain agent or chain that supports tool-calling.

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Quick Start Summary

  1. Sign up at app.paymanai.com to get your API Key.
  2. Install dependencies: 
    pip install paymanai langchain-community
  3. Export environment variables: 
    export PAYMAN_API_SECRET="YOUR_SECRET_KEY"
export PAYMAN_ENVIRONMENT="sandbox"
  4. Instantiate a PaymanAI tool, passing your desired name/description.
  5. Call the tool with .invoke(...) or integrate it into a chain or agent.

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API reference

You can find full API documentation for PaymanAI at:

​
Chaining

from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnableConfig, chain
from langchain.chat_models import init_chat_model

# Assume we've imported your PaymanAITool or multiple Payman AI Tools
payman_tool = PaymanAITool(name="send_payment")

# Build a prompt
prompt = ChatPromptTemplate([
    ("system", "You are a helpful AI that can send payments if asked."),
    ("human", "{user_input}"),
    ("placeholder", "{messages}"),
])

llm = init_chat_model(model="gpt-4", model_provider="openai")
llm_with_tools = llm.bind_tools([payman_tool], tool_choice=payman_tool.name)

llm_chain = prompt | llm_with_tools

@chain
def tool_chain(user_input: str, config: RunnableConfig):
    input_ = {"user_input": user_input}
    ai_msg = llm_chain.invoke(input_, config=config)
    tool_msgs = payman_tool.batch(ai_msg.tool_calls, config=config)
    return llm_chain.invoke({**input_, "messages": [ai_msg, *tool_msgs]}, config=config)

# Example usage:
response = tool_chain.invoke("Send $10 to payee123.")
print(response)```

## API reference

You can find full API documentation for PaymanAI at:

- [Python reference](https://python.langchain.com/v0.2/api_reference/community/tools/langchain_community.tools.langchain_payman_tool.tool.PaymanAI.html)
- (Any other relevant references or doc links)