Mastra Framework Guide

### Building an AI Agent for Customer Support with Mastra Framework

#### **Step 1: Setup and Authentication**
First, ensure you have the latest Mastra SDK installed:
```bash
pip install mastra-sdk --upgrade
```
Next, authenticate using your API key:
```python
from mastra import MastraClient
client = MastraClient(api_key="your_api_key_here")
```
*Verify the [Mastra Authentication Docs](https://docs.mastra.ai/auth) for the latest token expiration policies.*

#### **Step 2: Define the Agent Workflow**
Design a workflow for handling customer support queries. Use the `Workflow` class to structure the agent:
```python
from mastra.workflows import Workflow

support_workflow = Workflow(
    name="Customer Support Agent",
    description="Handles customer queries and routes to appropriate teams.",
    steps=[
        {"name": "intake", "type": "input", "handler": "text_input"},
        {"name": "classify", "type": "llm", "model": "gpt-4", "prompt": "Classify the query as billing, technical, or general."},
        {"name": "route", "type": "conditional", "conditions": {"billing": "billing_team", "technical": "tech_team"}}
    ]
)
```

#### **Step 3: Integrate External Tools**
Add tools like a CRM lookup or email sender. Example:
```python
from mastra.tools import HttpTool

crm_lookup = HttpTool(
    name="CRM Lookup",
    url="https://api.[COMPANY].com/crm",
    method="GET",
    auth="bearer_token"
)

support_workflow.add_tool(crm_lookup)
```

#### **Step 4: Deploy and Monitor**
Deploy the agent using Mastra’s CLI:
```bash
mastra deploy --workflow support_workflow.yaml
```
Monitor performance via the Mastra Dashboard and adjust workflows based on feedback.