> ## Documentation Index
> Fetch the complete documentation index at: https://thethirdpenco-feat-tool-lifecycle-events.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Vercel Adapter

> API reference for the Vercel handle_vercel adapter

The Vercel adapter enables deploying agents as serverless functions on Vercel's edge platform.

## Import

```python theme={null}
from ai_query.adapters.vercel import handle_vercel
```

***

## handle\_vercel

The `handle_vercel` function bridges Vercel's HTTP handler to the agent system.

### Function Signature

```python theme={null}
def handle_vercel(agent: Agent, handler: BaseHTTPRequestHandler) -> None
```

#### Parameters

<ParamField path="agent" type="Agent" required>
  The agent instance to handle requests.
</ParamField>

<ParamField path="handler" type="BaseHTTPRequestHandler" required>
  Vercel's HTTP handler instance.
</ParamField>

### Usage Examples

#### Basic Vercel API Route

```python theme={null}
# api/index.py
from http.server import BaseHTTPRequestHandler
from ai_query.agents import Agent
from ai_query.adapters.vercel import handle_vercel
from ai_query.providers import openai

# Create agent
agent = Agent(
    "vercel-bot",
    model=openai("gpt-4o"),
    system="You are a Vercel-hosted assistant."
)

class handler(BaseHTTPRequestHandler):
    def do_POST(self):
        handle_vercel(agent, self)

    def do_GET(self):
        handle_vercel(agent, self)
```

#### Multiple Endpoints

```python theme={null}
# api/chat.py
from http.server import BaseHTTPRequestHandler
from ai_query.agents import Agent
from ai_query.adapters.vercel import handle_vercel
from ai_query.providers import openai

chat_agent = Agent("chat-agent", model=openai("gpt-4o"))

class handler(BaseHTTPRequestHandler):
    def do_POST(self):
        handle_vercel(chat_agent, self)

# api/research.py
research_agent = Agent("research-agent", model=openai("gpt-4o"))

class handler(BaseHTTPRequestHandler):
    def do_POST(self):
        handle_vercel(research_agent, self)
```

#### With Environment Variables

```python theme={null}
import os
from http.server import BaseHTTPRequestHandler
from ai_query.agents import Agent
from ai_query.adapters.vercel import handle_vercel
from ai_query.providers import openai

agent = Agent(
    "vercel-agent",
    model=openai(os.getenv("OPENAI_MODEL", "gpt-4o")),
    system=os.getenv("SYSTEM_PROMPT", "You are helpful.")
)

class handler(BaseHTTPRequestHandler):
    def do_POST(self):
        handle_vercel(agent, self)
```

***

## Project Structure

```
my-vercel-app/
├── api/
│   ├── index.py          # Main agent
│   ├── chat.py           # Chat agent
│   └── research.py       # Research agent
├── agents/
│   ├── __init__.py
│   ├── chat_agent.py
│   └── research_agent.py
├── package.json
└── vercel.json
```

```python theme={null}
# api/index.py
from http.server import BaseHTTPRequestHandler
from agents.chat_agent import create_chat_agent
from ai_query.adapters.vercel import handle_vercel

agent = create_chat_agent()

class handler(BaseHTTPRequestHandler):
    def do_POST(self):
        handle_vercel(agent, self)
    def do_GET(self):
        handle_vercel(agent, self)
```

***

## Error Handling

The Vercel adapter returns a plain text error response:

```
"Invalid JSON body"
```

For custom error handling, wrap the agent in your handler class.