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docs: add payman docs (#29362)
- **Description:** Adding the docs to use the payman-langchain integration :)
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docs/docs/integrations/providers/payman-tool.mdx
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115
docs/docs/integrations/providers/payman-tool.mdx
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# PaymanAI
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PaymanAI provides functionality to send and receive payments (fiat and crypto) on behalf of an AI Agent. To get started:
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1. **Sign up** at app.paymanai.com to create an AI Agent and obtain your **API Key**.
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2. **Set** environment variables (`PAYMAN_API_SECRET` for your API Key, `PAYMAN_ENVIRONMENT` for sandbox or production).
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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
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The PaymanAI integration is part of the `langchain-community` (or your custom) package. It allows you to:
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- Send payments (`send_payment`) to crypto addresses or bank accounts.
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- Search for payees (`search_payees`).
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- Add new payees (`add_payee`).
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- Request money from customers with a hosted checkout link (`ask_for_money`).
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- Check agent or customer balances (`get_balance`).
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These can be wrapped as **LangChain Tools** for an LLM-based agent to call them automatically.
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### Integration details
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| Class | Package | Serializable | JS support | Package latest |
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| :--- | :--- | :---: | :---: | :--- |
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| PaymanAI | `langchain_community` | ❌ | ❌ | [PyPI Version] |
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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
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1. **Install** the `langchain-community` (or equivalent) package:
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```bash
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pip install --quiet -U langchain-community
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```
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2. **Install** the PaymanAI SDK:
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```bash
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pip install paymanai
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```
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3. **Set** environment variables:
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```bash
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export PAYMAN_API_SECRET="YOUR_SECRET_KEY"
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export PAYMAN_ENVIRONMENT="sandbox"
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```
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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
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Here is an example of instantiating a PaymanAI tool. If you have multiple Payman methods, you can create multiple tools.
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```python
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from langchain_community.tools.langchain_payman_tool.tool import PaymanAI
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# Instantiate the PaymanAI tool (example)
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tool = PaymanAI(
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name="send_payment",
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description="Send a payment to a specified payee.",
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)
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```
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## Invocation
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### Invoke directly with args
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You can call `tool.invoke(...)` and pass a dictionary matching the tool's expected fields. For example:
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```python
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response = tool.invoke({
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"amount_decimal": 10.00,
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"payment_destination_id": "abc123",
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"customer_id": "cust_001",
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"memo": "Payment for invoice #XYZ"
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})
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```
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### Invoke with ToolCall
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When used inside an AI workflow, the LLM might produce a `ToolCall` dict. You can simulate it as follows:
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```python
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model_generated_tool_call = {
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"args": {
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"amount_decimal": 10.00,
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"payment_destination_id": "abc123"
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},
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"id": "1",
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"name": tool.name,
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"type": "tool_call",
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}
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tool.invoke(model_generated_tool_call)
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```
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## Using the Tool in a Chain or Agent
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You can bind a PaymanAI tool to a LangChain agent or chain that supports tool-calling.
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## Quick Start Summary
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1. **Sign up** at app.paymanai.com to get your **API Key**.
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2. **Install** dependencies:
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```bash
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pip install paymanai langchain-community
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```
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3. **Export** environment variables:
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```bash
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export PAYMAN_API_SECRET="YOUR_SECRET_KEY"
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export PAYMAN_ENVIRONMENT="sandbox"
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```
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4. **Instantiate** a PaymanAI tool, passing your desired name/description.
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5. **Call** the tool with `.invoke(...)` or integrate it into a chain or agent.
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189
docs/docs/integrations/tools/payman-tool.ipynb
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189
docs/docs/integrations/tools/payman-tool.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"# PaymanAI\n",
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"\n",
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"PaymanAI provides functionality to send and receive payments (fiat and crypto) on behalf of an AI Agent. To get started:\n",
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"\n",
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"1. **Sign up** at app.paymanai.com to create an AI Agent and obtain your **API Key**.\n",
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"2. **Set** environment variables (`PAYMAN_API_SECRET` for your API Key, `PAYMAN_ENVIRONMENT` for sandbox or production).\n",
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"\n",
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"This notebook gives a quick overview of integrating PaymanAI into LangChain as a tool. For complete reference, see the API documentation.\n",
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"\n",
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"## Overview\n",
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"\n",
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"The PaymanAI integration is part of the `langchain-community` (or your custom) package. It allows you to:\n",
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"\n",
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"- Send payments (`send_payment`) to crypto addresses or bank accounts.\n",
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"- Search for payees (`search_payees`).\n",
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"- Add new payees (`add_payee`).\n",
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"- Request money from customers with a hosted checkout link (`ask_for_money`).\n",
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"- Check agent or customer balances (`get_balance`).\n",
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"\n",
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"These can be wrapped as **LangChain Tools** for an LLM-based agent to call them automatically.\n",
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"\n",
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"### Integration details\n",
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"\n",
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"| Class | Package | Serializable | JS support | Package latest |\n",
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"| :--- | :--- | :---: | :---: | :--- |\n",
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"| PaymanAI | `langchain_community` | ❌ | ❌ | [PyPI Version] |\n",
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"\n",
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"If you're simply calling the PaymanAI SDK, you can do it directly or via the **Tool** interface in LangChain.\n",
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"\n",
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"## Setup\n",
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"\n",
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"1. **Install** the `langchain-community` (or equivalent) package:\n",
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"\n",
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"```bash\n",
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"pip install --quiet -U langchain-community\n",
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"```\n",
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"\n",
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"2. **Install** the PaymanAI SDK:\n",
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"```bash\n",
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"pip install paymanai\n",
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"```\n",
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"\n",
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"3. **Set** environment variables:\n",
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"```bash\n",
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"export PAYMAN_API_SECRET=\"YOUR_SECRET_KEY\"\n",
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"export PAYMAN_ENVIRONMENT=\"sandbox\"\n",
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"```\n",
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"\n",
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"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.\n",
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"\n",
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"## Instantiation\n",
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"\n",
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"Here is an example of instantiating a PaymanAI tool. If you have multiple Payman methods, you can create multiple tools.\n",
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"\n",
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"```python\n",
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"from langchain_community.tools.langchain_payman_tool.tool import PaymanAI\n",
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"\n",
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"# Instantiate the PaymanAI tool (example)\n",
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"tool = PaymanAI(\n",
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" name=\"send_payment\",\n",
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" description=\"Send a payment to a specified payee.\",\n",
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")\n",
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"```\n",
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"\n",
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"## Invocation\n",
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"\n",
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"### Invoke directly with args\n",
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"\n",
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"You can call `tool.invoke(...)` and pass a dictionary matching the tool's expected fields. For example:\n",
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"\n",
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"```python\n",
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"response = tool.invoke({\n",
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" \"amount_decimal\": 10.00,\n",
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" \"payment_destination_id\": \"abc123\",\n",
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" \"customer_id\": \"cust_001\",\n",
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" \"memo\": \"Payment for invoice #XYZ\"\n",
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"})\n",
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"```\n",
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"\n",
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"### Invoke with ToolCall\n",
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"\n",
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"When used inside an AI workflow, the LLM might produce a `ToolCall` dict. You can simulate it as follows:\n",
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"\n",
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"```python\n",
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"model_generated_tool_call = {\n",
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" \"args\": {\n",
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" \"amount_decimal\": 10.00,\n",
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" \"payment_destination_id\": \"abc123\"\n",
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" },\n",
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" \"id\": \"1\",\n",
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" \"name\": tool.name,\n",
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" \"type\": \"tool_call\",\n",
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"}\n",
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"tool.invoke(model_generated_tool_call)\n",
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"```\n",
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"\n",
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"## Using the Tool in a Chain or Agent\n",
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"\n",
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"You can bind a PaymanAI tool to a LangChain agent or chain that supports tool-calling.\n",
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"\n",
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"## Quick Start Summary\n",
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"\n",
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"1. **Sign up** at app.paymanai.com to get your **API Key**.\n",
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"2. **Install** dependencies:\n",
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" ```bash\n",
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" pip install paymanai langchain-community\n",
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" ```\n",
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"3. **Export** environment variables:\n",
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" ```bash\n",
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" export PAYMAN_API_SECRET=\"YOUR_SECRET_KEY\"\n",
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" export PAYMAN_ENVIRONMENT=\"sandbox\"\n",
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" ```\n",
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"4. **Instantiate** a PaymanAI tool, passing your desired name/description.\n",
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"5. **Call** the tool with `.invoke(...)` or integrate it into a chain or agent."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## API reference\n",
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"\n",
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"You can find full API documentation for PaymanAI at:\n",
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"\n",
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"- [Langchain-Payman Python reference](https://pypi.org/project/langchain-payman-tool/)\n",
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"- [Payman Docs](https://docs.paymanai.com)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Chaining\n",
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"\n",
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"```python\n",
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"from langchain_core.prompts import ChatPromptTemplate\n",
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"from langchain_core.runnables import RunnableConfig, chain\n",
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"from langchain.chat_models import init_chat_model\n",
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"\n",
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"# Assume we've imported your PaymanAITool or multiple Payman AI Tools\n",
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"payman_tool = PaymanAITool(name=\"send_payment\")\n",
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"\n",
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"# Build a prompt\n",
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"prompt = ChatPromptTemplate([\n",
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" (\"system\", \"You are a helpful AI that can send payments if asked.\"),\n",
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" (\"human\", \"{user_input}\"),\n",
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" (\"placeholder\", \"{messages}\"),\n",
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"])\n",
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"\n",
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"llm = init_chat_model(model=\"gpt-4\", model_provider=\"openai\")\n",
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"llm_with_tools = llm.bind_tools([payman_tool], tool_choice=payman_tool.name)\n",
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"\n",
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"llm_chain = prompt | llm_with_tools\n",
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"\n",
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"@chain\n",
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"def tool_chain(user_input: str, config: RunnableConfig):\n",
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" input_ = {\"user_input\": user_input}\n",
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" ai_msg = llm_chain.invoke(input_, config=config)\n",
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" tool_msgs = payman_tool.batch(ai_msg.tool_calls, config=config)\n",
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" return llm_chain.invoke({**input_, \"messages\": [ai_msg, *tool_msgs]}, config=config)\n",
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"\n",
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"# Example usage:\n",
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"response = tool_chain.invoke(\"Send $10 to payee123.\")\n",
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"print(response)```\n",
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"\n",
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"## API reference\n",
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"\n",
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"You can find full API documentation for PaymanAI at:\n",
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"\n",
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"- [Python reference](https://python.langchain.com/v0.2/api_reference/community/tools/langchain_community.tools.langchain_payman_tool.tool.PaymanAI.html)\n",
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"- (Any other relevant references or doc links)"
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]
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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@ -350,3 +350,8 @@ packages:
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path: .
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repo: pipeshift-org/langchain-pipeshift
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downloads: 115
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- name: langchain-payman-tool
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path: .
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repo: paymanai/langchain-payman-tool
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downloads: 0
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downloads_updated_at: "2025-01-22T00:00:00+00:00"
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